Tootfinder

"Amazon’s burning approach to unsold and returned products"
#Amazon #Retail
h…

Amazon's burning approach to unsold and returned products | Ethical Consumer
In case you weren’t angry enough about Amazon’s systemic tax avoidance, this article is the first in a series where we talk about some of Amazon’s unsustainable and environmentally-damaging practices.

This https://arxiv.org/abs/2401.06662 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Sorting inversion sequences
We consider the avoidance of patterns in inversion sequences that relate sorting via sorting machines including data structures such as pop stacks and stacks. Such machines have been studied under a variety of additional constraints and generalizations, some of which we apply here. We give the classification of several classes of sortable inversion sequences in terms of pattern avoidance. We are able to provide an exact enumeration of some of the sortable classes in question using both classica…

#GettingReal is now more mobile friendly.
Alternative manifesto, given the political parties' avoidance of the real issues, or failure to tackle them at the scale required.
#UKPolitics
#ClimateCrisis

A Novel Optimization-Based Collision Avoidance For Autonomous On-Orbit Assembly
Siavash Tavana, Sepideh Faghihi, Anton de Ruiter, Krishna Dev Kumar
https://arxiv.org/abs/2404.07916

A Novel Optimization-Based Collision Avoidance For Autonomous On-Orbit Assembly
The collision avoidance constraints are prominent as non-convex, non-differentiable, and challenging when defined in optimization-based motion planning problems. To overcome these issues, this paper presents a novel non-conservative collision avoidance technique using the notion of convex optimization to establish the distance between robotic spacecraft and space structures for autonomous on-orbit assembly operations. The proposed technique defines each ellipsoidal- and polyhedral-shaped object…

Real-Time Sensor-Based Feedback Control for Obstacle Avoidance in Unknown Environments
Lyes Smaili, Soulaimane Berkane
https://arxiv.org/abs/2403.08614 htt…

Real-Time Sensor-Based Feedback Control for Obstacle Avoidance in Unknown Environments
We revisit the Safety Velocity Cones (SVCs) obstacle avoidance approach for real-time autonomous navigation in an unknown $n$-dimensional environment. We propose a locally Lipschitz continuous implementation of the SVC controller using the distance-to-the-obstacle function and its gradient. We then show that the proposed implementation guarantees safe navigation in generic environments and almost globally asymptotic stability (AGAS) of the desired destination when the workspace contains strongl…

"Amazon’s burning approach to unsold and returned products"
#Amazon #Retail
h…

Amazon's burning approach to unsold and returned products | Ethical Consumer
In case you weren’t angry enough about Amazon’s systemic tax avoidance, this article is the first in a series where we talk about some of Amazon’s unsustainable and environmentally-damaging practices.

This https://arxiv.org/abs/2403.03098 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Galaxies in the Zone of Avoidance: Misclassifications using machine learning tools
Automated methods for classifying extragalactic objects in large surveys offer significant advantages compared to manual approaches in terms of efficiency and consistency. However, the existence of the Galactic disk raises additional concerns. These regions are known for high levels of interstellar extinction, star crowding, and limited data sets and studies. In this study, we explore the identification and classification of galaxies in the Zone of Avoidance (ZoA). In particular, we compare our…

#GettingReal is now more mobile friendly.
Alternative manifesto, given the political parties' avoidance of the real issues, or failure to tackle them at the scale required.
#UKPolitics
#ClimateCrisis

This https://arxiv.org/abs/2306.08420 has been replaced.
link: https://scholar.google.com/scholar?q=a

Combinatorial generation via permutation languages. VI. Binary trees
In this paper we propose a notion of pattern avoidance in binary trees that generalizes the avoidance of contiguous tree patterns studied by Rowland and non-contiguous tree patterns studied by Dairyko, Pudwell, Tyner, and Wynn. Specifically, we propose algorithms for generating different classes of binary trees that are characterized by avoiding one or more of these generalized patterns. This is achieved by applying the recent Hartung-Hoang-Mütze-Williams generation framework, by encoding bina…

Real-Time Sensor-Based Feedback Control for Obstacle Avoidance in Unknown Environments
Lyes Smaili, Soulaimane Berkane
https://arxiv.org/abs/2403.08614 htt…

Real-Time Sensor-Based Feedback Control for Obstacle Avoidance in Unknown Environments
We revisit the Safety Velocity Cones (SVCs) obstacle avoidance approach for real-time autonomous navigation in an unknown $n$-dimensional environment. We propose a locally Lipschitz continuous implementation of the SVC controller using the distance-to-the-obstacle function and its gradient. We then show that the proposed implementation guarantees safe navigation in generic environments and almost globally asymptotic stability (AGAS) of the desired destination when the workspace contains strongl…

This https://arxiv.org/abs/2311.02817 has been replaced.
link: https://scholar.google.com/scholar?q=a

Safe-VLN: Collision Avoidance for Vision-and-Language Navigation of Autonomous Robots Operating in Continuous Environments
The task of vision-and-language navigation in continuous environments (VLN-CE) aims at training an autonomous agent to perform low-level actions to navigate through 3D continuous surroundings using visual observations and language instructions. The significant potential of VLN-CE for mobile robots has been demonstrated across a large number of studies. However, most existing works in VLN-CE focus primarily on transferring the standard discrete vision-and-language navigation (VLN) methods to con…

Partner selection and evolution of out-group avoidance
Hirofumi Takesue
https://arxiv.org/abs/2403.06893 https://arxiv.org/pdf/2403.0…

Partner selection and evolution of out-group avoidance
The preferential treatment of in-group members is widely observed. This study examines this phenomenon in the domain of cooperation in social dilemmas using evolutionary agent-based models that consider the role of partner selection. The model considers a repeated prisoner's dilemma game, in which agents belong to one of two groups that are distinguished by the continuation probability of pair interactions. On the basis of the behavior in the last round and the group affiliation of the partner,…

This https://arxiv.org/abs/2307.12786 has been replaced.
initial toot: https://mastoxiv.page/@…

Dimensionless Numbers Reveal Distinct Regimes in the Structure and Dynamics of Pedestrian Crowds
In fluid mechanics, dimensionless numbers like the Reynolds number help classify flows. We argue that such a classification is also relevant for crowd flows by putting forward the dimensionless Intrusion and Avoidance numbers.Using an extensive dataset, we show that these delineate regimes that are characterized by distinct structural signatures, best probed in terms of distances at low Avoidance number and times-to-collision at low Intrusion number.These findings prompt a perturbative expansio…

Series B, Episode 04 - Horizon
ZEN: Five hundred spacials.
BLAKE: Course and speed for avoidance?
https://blake.torpidity.net/s/204/14 📺 B7B3

For the avoidance of doubt, no one at all has a 'legitimate interest' in anything I do on the Web, and there is absolutely no need to keep asking whether I'm going to make an exception for your website.
I'm not.

This https://arxiv.org/abs/2309.07979 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Fast Safe Rectangular Corridor-based Online AGV Trajectory Optimization with Obstacle Avoidance
Automated Guided Vehicles (AGVs) are essential in various industries for their efficiency and adaptability. However, planning trajectories for AGVs in obstacle-dense, unstructured environments presents significant challenges due to the nonholonomic kinematics, abundant obstacles, and the scenario's nonconvex and constrained nature. To address this, we propose an efficient trajectory planning framework for AGVs by formulating the problem as an optimal control problem. Our framework utilizes the …

@eric@disabled.social I feel like my continued avoidance of LinkedIn is validated.

Disarray, reduced words, and 321-avoidance in George groups
Joel Brewster Lewis, Bridget Eileen Tenner
https://arxiv.org/abs/2404.06379 https://

Disarray, reduced words, and 321-avoidance in George groups
Previous work has shown that the disarray (or displacement) of an (affine) (signed) permutation is bounded in terms of its Coxeter length. Here, we characterize the permutations for which the bound is sharp in two ways: in terms of a natural property of their reduced words, and by ``globally'' avoiding the pattern 321.

The Guardian: #Trump Gave Top US Firms Staggering Tax Cuts, With Some Paying $0 or less – Report – ITEP
https://itep.org/the-guardian-trump-ga

The Guardian: Trump Gave Top US Firms Staggering Tax Cuts, With Some Paying $0 or less – Report
Some of the US’s most profitable corporations, including General Motors, Citigroup and Netflix, have slashed their tax bills in the years since the passage of the Trump tax cuts, with nearly a quarter paying rates in the single digits and 23 paying nothing, a report has found. The 2017 law cut the top corporate income tax rate from 35% to 21%. But the new assessment of corporate tax avoidance, published on Thursday by the non-profit Institute on Taxation and Economic Policy (Itep), found t…

Distributed MPC for autonomous ships on inland waterways with collaborative collision avoidance
Hoang Anh Tran, Tor Arne Johansen, Rudy R. Negenborn
https://arxiv.org/abs/2403.00554

Distributed MPC for autonomous ships on inland waterways with collaborative collision avoidance
This paper presents a distributed solution for the problem of collaborative collision avoidance for autonomous inland waterway ships. A two-layer collision avoidance framework that considers inland waterway traffic regulations is proposed to increase navigational safety for autonomous ships. Our approach allows for modifying traffic rules without changing the collision avoidance algorithm, and is based on a novel formulation of model predictive control (MPC) for collision avoidance of ships. Th…

📉 Researchers say 'loss avoidance' is all the rage in private equity
#finance

Researchers say 'loss avoidance' is all the rage in private equity
Private equity (PE) is known as a "high-risk, high-return" asset class. But as risk-averse institutional investors continue to up their stake in PE, private fund managers are expected to provide metrics that characterize the riskiness of their portfolios. Yet the lack of observable prices makes traditional measures of risk (such as standard deviation of periodic investment returns) entirely unsuitable.

Morphodynamics of chloroplast network control light-avoidance response in the non-motile dinoflagellate Pyrocystis lunula
Nico Schramma, Gloria Casas Canales, Maziyar Jalaal
https://arxiv.org/abs/2404.19570 https://arxiv.org/pdf/2404.19570
arXiv:2404.19570v1 Announce Type: new
Abstract: Photosynthetic algae play a significant role in oceanic carbon capture. Their performance, however, is constantly challenged by fluctuations in environmental light conditions. Here, we show that the non-motile single-celled marine dinoflagellate Pyrocystis lunula can internally contract its chloroplast network in response to light. By exposing the cell to various physiological light conditions and applying temporal illumination sequences, we find that network morphodynamics follows simple rules, as established in a mathematical model. Our analysis of the chloroplast structure reveals that its unusual reticulated morphology constitutes properties similar to auxetic metamaterials, facilitating drastic deformations for light-avoidance, while confined by the cell wall. Our study shows how the topologically complex network of chloroplasts is crucial in supporting the dinoflagellate's adaptation to varying light conditions, thereby facilitating essential life-sustaining processes.

A Neuromorphic Approach to Obstacle Avoidance in Robot Manipulation
Ahmed Faisal Abdelrahman, Matias Valdenegro-Toro, Maren Bennewitz, Paul G. Pl\"oger
https://arxiv.org/abs/2404.05858

A Neuromorphic Approach to Obstacle Avoidance in Robot Manipulation
Neuromorphic computing mimics computational principles of the brain in $\textit{silico}$ and motivates research into event-based vision and spiking neural networks (SNNs). Event cameras (ECs) exclusively capture local intensity changes and offer superior power consumption, response latencies, and dynamic ranges. SNNs replicate biological neuronal dynamics and have demonstrated potential as alternatives to conventional artificial neural networks (ANNs), such as in reducing energy expenditure and…

For the avoidance of doubt, it is to whet the appetite, not to wet the appetite.
#EnglishUsageAndAbusage

Galaxies in the Zone of Avoidance: Misclassifications using machine learning tools
P. Marchant Cort\'es, J. L. Nilo Castell\'on, M. V. Alonso, L. Baravalle, C. Villal\'on, M. A. Sgr\'o, I. V. Daza-Perilla, M. Soto, F. Milla Castro, D. Minniti, N. Masetti, C. Valotto, M. Lares
https://arxiv.org/abs/2403.03098 https://arxiv.org/pdf/2403.03098
arXiv:2403.03098v1 Announce Type: new
Abstract: Automated methods for classifying extragalactic objects in large surveys offer significant advantages compared to manual approaches in terms of efficiency and consistency. However, the existence of the Galactic disk raises additional concerns. These regions are known for high levels of interstellar extinction, star crowding, and limited data sets and studies. In this study, we explore the identification and classification of galaxies in the Zone of Avoidance (ZoA). In particular, we compare our results in the near-infrared with X-ray data. We analize the appearance of the objects classified as galaxies using machine learning by Zhang et al. (2021) in the Galactic disk and make a comparison with the visually confirmed galaxies from the VVV NIRGC (Baravalle et al. (2021). Our analysis, which includes the visual inspection of all sources catalogued as galaxies throughout the Galactic disk using machine learning techniques reveals significant differences. Only 4 galaxies were found in both the near-Infrared and X-ray data sets. Several specific regions of interest within the ZoA exhibit a high probability of being galaxies in X-ray data but closely resemble extended Galactic objects. The results indicate the difficulty of using machine learning methods for galaxy classification in the ZoA mainly due to the scarce information on galaxies behind the Galactic plane in the training set. They also stress the importance of considering specific factors that are present to improve the reliability and accuracy of future studies in this challenging region.

Collision Avoidance Verification of Multiagent Systems with Learned Policies
Zihao Dong, Shayegan Omidshafiei, Michael Everett
https://arxiv.org/abs/2403.03314

Collision Avoidance Verification of Multiagent Systems with Learned Policies
For many multiagent control problems, neural networks (NNs) have enabled promising new capabilities. However, many of these systems lack formal guarantees (e.g., collision avoidance, robustness), which prevents leveraging these advances in safety-critical settings. While there is recent work on formal verification of NN-controlled systems, most existing techniques cannot handle scenarios with more than one agent. To address this research gap, this paper presents a backward reachability-based ap…

This https://arxiv.org/abs/2310.17762 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCC_…

Symmetric Exponential Time Requires Near-Maximum Circuit Size: Simplified, Truly Uniform
In a recent breakthrough, Chen, Hirahara and Ren prove that $\mathsf{S_2E}/_1 \not\subset \mathsf{SIZE}[2^n/n]$ by giving a single-valued $\mathsf{FS_2P}$ algorithm for the Range Avoidance Problem ($\mathsf{Avoid}$) that works for infinitely many input size $n$. Building on their work, we present a simple single-valued $\mathsf{FS_2P}$ algorithm for $\mathsf{Avoid}$ that works for all input size $n$. As a result, we obtain the circuit lower bound $\mathsf{S_2E} \not\subset {i.o.}$-$\mathsf{SI…

This https://arxiv.org/abs/2311.15327 has been replaced.
link: https://scholar.google.com/scholar?q=a

FRAC-Q-Learning: A Reinforcement Learning with Boredom Avoidance Processes for Social Robots
The reinforcement learning algorithms have often been applied to social robots. However, most reinforcement learning algorithms were not optimized for the use of social robots, and consequently they may bore users. We proposed a new reinforcement learning method specialized for the social robot, the FRAC-Q-learning, that can avoid user boredom. The proposed algorithm consists of a forgetting process in addition to randomizing and categorizing processes. This study evaluated interest and boredom…

This https://arxiv.org/abs/2203.16654 has been replaced.
link: https://scholar.google.com/scholar?q=a

Geographic Spines in the 2020 Census Disclosure Avoidance System
The 2020 Census Disclosure Avoidance System (DAS) is a formally private mechanism that first adds independent noise to cross tabulations for a set of pre-specified hierarchical geographic units, which is known as the geographic spine. After post-processing these noisy measurements, DAS outputs a formally private database with fields indicating location in the standard census geographic spine, which is defined by the United States as a whole, states, counties, census tracts, block groups, and ce…

Synthetic Census Data Generation via Multidimensional Multiset Sum
Cynthia Dwork, Kristjan Greenewald, Manish Raghavan
https://arxiv.org/abs/2404.10095 htt…

Synthetic Census Data Generation via Multidimensional Multiset Sum
The US Decennial Census provides valuable data for both research and policy purposes. Census data are subject to a variety of disclosure avoidance techniques prior to release in order to preserve respondent confidentiality. While many are interested in studying the impacts of disclosure avoidance methods on downstream analyses, particularly with the introduction of differential privacy in the 2020 Decennial Census, these efforts are limited by a critical lack of data: The underlying "microdata,…

Modeling of obstacle avoidance by a dense crowd as a Mean-Field Game
Matteo Butano, Thibault Bonnemain, C\'ecile Appert-Rolland, Alexandre Nicolas, Denis Ullmo
https://arxiv.org/abs/2403.00603

Modeling of obstacle avoidance by a dense crowd as a Mean-Field Game
In this paper we use a minimal model based on Mean-Field Games (a mathematical framework apt to describe situations where a large number of agents compete strategically) to simulate the scenario where a static dense human crowd is crossed by a cylindrical intruder. After a brief explanation of the mathematics behind it, we compare our model directly against the empirical data collected during a controlled experiment replicating the aforementioned situation. We then summarize the features that m…

This https://arxiv.org/abs/2305.04104 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Hybrid Feedback for Affine Nonlinear Systems with Application to Global Obstacle Avoidance (Extended Version)
This paper explores the design of hybrid feedback for a class of affine nonlinear systems with topological constraints that prevent global asymptotic stability. A new hybrid control strategy is introduced, which differs conceptually from the commonly used synergistic hybrid approaches. The key idea involves the construction of a generalized synergistic Lyapunov function whose switching variable can either remain constant or dynamically change between jumps. Based on this new hybrid mechanism, a…

Controlling Communications Quality in V2V Platooning: a TSN-like Slot-Based Scheduler Approach
Angelo Feraudo, Andrea Garbugli, Paolo Bellavista
https://arxiv.org/abs/2405.01301 <…

Controlling Communications Quality in V2V Platooning: a TSN-like Slot-Based Scheduler Approach
Connected vehicles, facilitated by Vehicle-to-Vehicle (V2V) communications, play a key role in enhancing road safety and traffic efficiency. However, V2V communications primarily rely on wireless protocols, such as Wi-Fi, that require additional collision avoidance mechanisms to better ensure bounded latency and reliability in critical scenarios. In this paper, we introduce a novel approach to address the challenge of message collision in V2V platooning through a slotted-based solution inspired…

Mixed Strategy Constraints in Continuous Games
Mel Krusniak, Forrest Laine
https://arxiv.org/abs/2402.17874 https://arxiv.org/pdf/240…

Mixed Strategy Constraints in Continuous Games
Equilibrium problems representing interaction in physical environments typically require continuous strategies which satisfy opponent-dependent constraints, such as those modeling collision avoidance. However, as with finite games, mixed strategies are often desired, both from an equilibrium existence perspective as well as a competitive perspective. To that end, this work investigates a chance-constraint-based approach to coupled constraints in generalized Nash equilibrium problems which are s…

This https://arxiv.org/abs/2402.11799 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning
Collision avoidance algorithms for Autonomous Surface Vehicles (ASV) that follow the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) have been proposed in recent years. However, it may be difficult and unsafe to follow COLREGs in congested waters, where multiple ASVs are navigating in the presence of static obstacles and strong currents, due to the complex interactions. To address this problem, we propose a decentralized multi-ASV collision avoidance polic…

Obstacle Avoidance of Autonomous Vehicles: An LPVMPC with Scheduling Trust Region
Maryam Nezami, Dimitrios S. Karachalios, Georg Schildbach, Hossam S. Abbas
https://arxiv.org/abs/2405.02030

Obstacle Avoidance of Autonomous Vehicles: An LPVMPC with Scheduling Trust Region
Reference tracking and obstacle avoidance rank among the foremost challenging aspects of autonomous driving. This paper proposes control designs for solving reference tracking problems in autonomous driving tasks while considering static obstacles. We suggest a model predictive control (MPC) strategy that evades the computational burden of nonlinear nonconvex optimization methods after embedding the nonlinear model equivalently to a linear parameter-varying (LPV) formulation using the so-called…

This https://arxiv.org/abs/2312.09633 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Natural Gradient Variational Bayes without Fisher Matrix Analytic Calculation and Its Inversion
This paper introduces a method for efficiently approximating the inverse of the Fisher information matrix, a crucial step in achieving effective variational Bayes inference. A notable aspect of our approach is the avoidance of analytically computing the Fisher information matrix and its explicit inversion. Instead, we introduce an iterative procedure for generating a sequence of matrices that converge to the inverse of Fisher information. The natural gradient variational Bayes algorithm without…

This https://arxiv.org/abs/2402.11799 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning
Collision avoidance algorithms for Autonomous Surface Vehicles (ASV) that follow the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) have been proposed in recent years. However, it may be difficult and unsafe to follow COLREGs in congested waters, where multiple ASVs are navigating in the presence of static obstacles and strong currents, due to the complex interactions. To address this problem, we propose a decentralized multi-ASV collision avoidance polic…

This https://arxiv.org/abs/2311.18107 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Stochastic-Geometrical Framework for Object Pose Estimation based on Mixture Models Avoiding the Correspondence Problem
Background: Pose estimation of rigid objects is a practical challenge in optical metrology and computer vision. This paper presents a novel stochastic-geometrical modeling framework for object pose estimation based on observing multiple feature points. Methods: This framework utilizes mixture models for feature point densities in object space and for interpreting real measurements. Advantages are the avoidance to resolve individual feature correspondences and to incorporate correct stochastic…

Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions
Tamas G. Molnar, Suresh K. Kannan, James Cunningham, Kyle Dunlap, Kerianne L. Hobbs, Aaron D. Ames
https://arxiv.org/abs/2403.02508

Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions
Safety-critical failures often have fatal consequences in aerospace control. Control systems on aircraft, therefore, must ensure the strict satisfaction of safety constraints, preferably with formal guarantees of safe behavior. This paper establishes the safety-critical control of fixed-wing aircraft in collision avoidance and geofencing tasks. A control framework is developed wherein a run-time assurance (RTA) system modulates the nominal flight controller of the aircraft whenever necessary to…

This https://arxiv.org/abs/2402.00012 has been replaced.
link: https://scholar.google.com/scholar?q=a

On generalized covering and avoidance properties of finite groups and saturated fusion systems
A subgroup $A$ of a finite group $G$ is said to be a $CAP$-subgroup of $G$, if for any chief factor $H/K$ of $G$, either $A H= AK$ or $A\cap H = A \cap K$. Let $p$ be a prime, $S$ be a $p$-group and $\mathcal{F}$ be a saturated fusion system over $S$. Then $\mathcal{F}$ is said to be supersolvable, if there exists a series of $S$, namely $1 = S_0 \leq S_1 \leq \cdots \leq S_n = S$, such that $S_{i+1}/S_i$ is cyclic, and $S_i$ is strongly $\mathcal{F}$-closed for any $i=0,1,\cdots,n$. In this pa…

This https://arxiv.org/abs/2401.13966 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

The Avoidance Principle for Noncompact Hypersurfaces Moving by Mean Curvature Flow
Consider a pair of smooth, possibly noncompact, properly immersed hypersurfaces moving by mean curvature flow, or, more generally, a pair of weak set flows. We prove that if the ambient space is Euclidean space and if the distance between the two surfaces is initially nonzero, then the surfaces remain disjoint at all subsequent times. We prove the same result when the ambient space is a complete Riemannian manifold of nonzero injectivity radius, provided the curvature tensor (of the ambient spa…

This https://arxiv.org/abs/2401.17048 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Exploring Spatial Segregation Induced by Competition Avoidance as Driving Mechanism for Emergent Coexistence in Microbial Communities
This study investigates the role of spatial segregation, prompted by competition avoidance, as a key mechanism for emergent coexistence within microbial communities. Recognizing these communities as complex adaptive systems, we challenge the sufficiency of mean-field pairwise interaction models and consider the impact of spatial dynamics. We developed an individual-based spatial simulation depicting bacterial movement through a pattern of random walks influenced by competition avoidance, leadin…

This https://arxiv.org/abs/2309.06518 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Pattern Avoidance in Weak Ascent Sequences
In this paper, we study pattern avoidance in weak ascent sequences, giving some results for patterns of length 3. This is an analogous study to one given by Duncan and Steingrímsson for ascent sequences \cite{DS}. More precisely, we provide systematically the generating functions for the number of weak ascent sequences avoiding the patterns $001, 011, 012, 021$, and $102$. Additionally, we establish bijective connections between pattern-avoiding weak ascent sequences and other combinatorial ob…

Mathematical and computational framework for moving and colliding rigid bodies in a Newtonian fluid
C\'eline Van LandeghemIRMA, Luca BertiIRMA, Vincent ChabannesIRMA, Christophe Prud'HommeIRMA, Agathe ChouippeICube, Yannick HoarauICube, La\"etitia GiraldiCALISTO
https://arxiv.org/abs/2402.19093

Mathematical and computational framework for moving and colliding rigid bodies in a Newtonian fluid
We studied numerically the dynamics of colliding rigid bodies in a Newtonian fluid. The finite element method is used to solve the fluid-body interaction and the fluid motion is described in the Arbitrary-Lagrangian-Eulerian framework. To model the interactions between bodies, we consider a repulsive collision-avoidance model, defined by R. Glowinski. The main emphasis in this work is the generalization of this collision model to multiple rigid bodies of arbitrary shape. Our model first uses a …

This https://arxiv.org/abs/2303.10526 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

Efficient deadlock avoidance for 2D mesh NoCs that use OQ or VOQ routers
Network-on-chips (NoCs) are currently a widely used approach for achieving scalability of multi-cores to many-cores, as well as for interconnecting other vital system-on-chip (SoC) components. Each entity in 2D mesh-based NoCs has a router responsible for forwarding packets between the dimensions as well as the entity itself, and it is essentially a 5-port switch. With respect to the routing algorithm, there are important trade-offs between routing performance and the efficiency of overcoming p…

Interaction-Aware Vehicle Motion Planning with Collision Avoidance Constraints in Highway Traffic
Dongryul Kim, Hyeonjeong Kim, Kyoungseok Han
https://arxiv.org/abs/2404.01661

Interaction-Aware Vehicle Motion Planning with Collision Avoidance Constraints in Highway Traffic
This paper proposes collision-free optimal trajectory planning for autonomous vehicles in highway traffic, where vehicles need to deal with the interaction among each other. To address this issue, a novel optimal control framework is suggested, which couples the trajectory of surrounding vehicles with collision avoidance constraints. Additionally, we describe a trajectory optimization technique under state constraints, utilizing a planner based on Pontryagin's Minimum Principle, capable of nume…

Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions
Tamas G. Molnar, Suresh K. Kannan, James Cunningham, Kyle Dunlap, Kerianne L. Hobbs, Aaron D. Ames
https://arxiv.org/abs/2403.02508

Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions
Safety-critical failures often have fatal consequences in aerospace control. Control systems on aircraft, therefore, must ensure the strict satisfaction of safety constraints, preferably with formal guarantees of safe behavior. This paper establishes the safety-critical control of fixed-wing aircraft in collision avoidance and geofencing tasks. A control framework is developed wherein a run-time assurance (RTA) system modulates the nominal flight controller of the aircraft whenever necessary to…

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning
Ruihua Han, Shuai Wang, Shuaijun Wang, Zeqing Zhang, Jianjun Chen, Shijie Lin, Chengyang Li, Chengzhong Xu, Yonina C. Eldar, Qi Hao, Jia Pan
https://arxiv.org/abs/2403.06828

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning
Navigating a nonholonomic robot in a cluttered environment requires extremely accurate perception and locomotion for collision avoidance. This paper presents NeuPAN: a real-time, highly-accurate, map-free, robot-agnostic, and environment-invariant robot navigation solution. Leveraging a tightly-coupled perception-locomotion framework, NeuPAN has two key innovations compared to existing approaches: 1) it directly maps raw points to a learned multi-frame distance space, avoiding error propagation…

This https://arxiv.org/abs/2403.02508 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions
Safety-critical failures often have fatal consequences in aerospace control. Control systems on aircraft, therefore, must ensure the strict satisfaction of safety constraints, preferably with formal guarantees of safe behavior. This paper establishes the safety-critical control of fixed-wing aircraft in collision avoidance and geofencing tasks. A control framework is developed wherein a run-time assurance (RTA) system modulates the nominal flight controller of the aircraft whenever necessary to…

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning
Ruihua Han, Shuai Wang, Shuaijun Wang, Zeqing Zhang, Jianjun Chen, Shijie Lin, Chengyang Li, Chengzhong Xu, Yonina C. Eldar, Qi Hao, Jia Pan
https://arxiv.org/abs/2403.06828

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning
Navigating a nonholonomic robot in a cluttered environment requires extremely accurate perception and locomotion for collision avoidance. This paper presents NeuPAN: a real-time, highly-accurate, map-free, robot-agnostic, and environment-invariant robot navigation solution. Leveraging a tightly-coupled perception-locomotion framework, NeuPAN has two key innovations compared to existing approaches: 1) it directly maps raw points to a learned multi-frame distance space, avoiding error propagation…

Robot Safe Planning In Dynamic Environments Based On Model Predictive Control Using Control Barrier Function
Zetao Lu, Kaijun Feng, Jun Xu, Haoyao Chen, Yunjiang Lou
https://arxiv.org/abs/2404.05952

Robot Safe Planning In Dynamic Environments Based On Model Predictive Control Using Control Barrier Function
Implementing obstacle avoidance in dynamic environments is a challenging problem for robots. Model predictive control (MPC) is a popular strategy for dealing with this type of problem, and recent work mainly uses control barrier function (CBF) as hard constraints to ensure that the system state remains in the safe set. However, in crowded scenarios, effective solutions may not be obtained due to infeasibility problems, resulting in degraded controller performance. We propose a new MPC framework…

On the permutations that strongly avoid the pattern 312 or 231
Junyao Pan, Pengfei Guo
https://arxiv.org/abs/2404.01597 https://arxiv…

On the permutations that strongly avoid the pattern 312 or 231
In 2019, Bóna and Smith introduced the notion of \emph{strong pattern avoidance}, that is, a permutation and its square both avoid a given pattern. In this paper, we enumerate the set of permutations $π$ which not only strongly avoid the pattern $312$ or $231$ but also avoid the pattern $τ$, for $τ\in S_3$ and some $τ\in S_4$. One of them is to give a positive answer to a conjecture of Archer and Geary.

Memory signatures in path curvature of self-avoidant model particles are revealed by time delayed self mutual information
Katherine Daftari, Katherine Newhall
https://arxiv.org/abs/2403.19393

Memory signatures in path curvature of self-avoidant model particles are revealed by time delayed self mutual information
Emergent behavior in active systems is a complex byproduct of local, often pairwise, interactions. One such interaction is self-avoidance, which experimentally can arise as a response to self-generated environmental signals; such experiments have inspired non-Markovian mathematical models. In previous work, we set out to find ``hallmarks of self-avoidant memory" in a particle model for environmentally responsive swimming droplets. In our analysis, we found that transient self-trapping was a spa…

What comes after optical-bypass network? A study on optical-computing-enabled network
Dao Thanh Hai
https://arxiv.org/abs/2402.14970 https://

What comes after optical-bypass network? A study on optical-computing-enabled network
A new architectural paradigm, named, optical-computing-enabled network, is proposed as a potential evolution of the currently used optical-bypass framework. The main idea is to leverage the optical computing capabilities performed on transitional lightpaths at intermediate nodes and such proposal reverses the conventional wisdom in optical-bypass network, that is, separating in-transit lightpaths in avoidance of unwanted interference. In optical-computing-enabled network, the optical nodes are …

Low-cost adaptive obstacle avoidance trajectory control for express delivery drone
Yanhui Zhang, Caisheng Wei, Yifan Zhang, Congcong Tian, Weifang Chen
https://arxiv.org/abs/2403.19956

Low-cost adaptive obstacle avoidance trajectory control for express delivery drone
This paper studies quadcopters obstacle avoidance trajectory control (OATC) problem for express delivery. A new nonlinear adaptive learning controller that is low-cost and portable to different wheelbase sizes is proposed to adapt to large-angle maneuvers and load changes in UAV delivery missions. The controller consists of a nonlinear variable gain (NLVG) function and an extreme value search (ES) algorithm to reduce overshoot and settling time. Finally, simulations were conducted on a quadcopt…

This https://arxiv.org/abs/2209.01710 has been replaced.
link: https://scholar.google.com/scholar?q=a

Perception Simplex: Verifiable Collision Avoidance in Autonomous Vehicles Amidst Obstacle Detection Faults
Advances in deep learning have revolutionized cyber-physical applications, including the development of Autonomous Vehicles. However, real-world collisions involving autonomous control of vehicles have raised significant safety concerns regarding the use of Deep Neural Networks (DNN) in safety-critical tasks, particularly Perception. The inherent unverifiability of DNNs poses a key challenge in ensuring their safe and reliable operation. In this work, we propose Perception Simplex (PS), a fau…

This https://arxiv.org/abs/2209.01710 has been replaced.
link: https://scholar.google.com/scholar?q=a

Perception Simplex: Verifiable Collision Avoidance in Autonomous Vehicles Amidst Obstacle Detection Faults
Advances in deep learning have revolutionized cyber-physical applications, including the development of Autonomous Vehicles. However, real-world collisions involving autonomous control of vehicles have raised significant safety concerns regarding the use of Deep Neural Networks (DNN) in safety-critical tasks, particularly Perception. The inherent unverifiability of DNNs poses a key challenge in ensuring their safe and reliable operation. In this work, we propose Perception Simplex (PS), a fau…

This https://arxiv.org/abs/2302.12439 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Simultaneous upper and lower bounds of American option prices with hedging via neural networks
In this paper, we introduce two methods to solve the American-style option pricing problem and its dual form at the same time using neural networks. Without applying nested Monte Carlo, the first method uses a series of neural networks to simultaneously compute both the lower and upper bounds of the option price, and the second one accomplishes the same goal with one global network. The avoidance of extra simulations and the use of neural networks significantly reduce the computational complexi…

This https://arxiv.org/abs/2309.13285 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learning
End-to-end deep reinforcement learning (DRL) for quadrotor control promises many benefits -- easy deployment, task generalization and real-time execution capability. Prior end-to-end DRL-based methods have showcased the ability to deploy learned controllers onto single quadrotors or quadrotor teams maneuvering in simple, obstacle-free environments. However, the addition of obstacles increases the number of possible interactions exponentially, thereby increasing the difficulty of training RL pol…

Biological computations: limitations of attractor-based formalisms and the need for transients
Daniel Koch, Akhilesh Nandan, Gayathri Ramesan, Aneta Koseska
https://arxiv.org/abs/2404.10369

Biological computations: limitations of attractor-based formalisms and the need for transients
Living systems, from single cells to higher vertebrates, receive a continuous stream of non-stationary inputs that they sense, e.g., via cell surface receptors or sensory organs. Integrating these time-varying, multi-sensory, and often noisy information with memory using complex molecular or neuronal networks, they generate a variety of responses beyond simple stimulus-response association, including avoidance behavior, life-long-learning or social interactions. In a broad sense, these processe…

This https://arxiv.org/abs/2112.13400 has been replaced.
link: https://scholar.google.com/scholar?q=a

Parabolic Tamari Lattices in Linear Type B
We study parabolic aligned elements associated with the type-$B$ Coxeter group and the so-called linear Coxeter element. These elements were introduced algebraically in (Mühle and Williams, 2019) for parabolic quotients of finite Coxeter groups and were characterized by a certain forcing condition on inversions. We focus on the type-$B$ case and give a combinatorial model for these elements in terms of pattern avoidance. Moreover, we describe an equivalence relation on parabolic quotients of t…

This https://arxiv.org/abs/2403.03314 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Collision Avoidance Verification of Multiagent Systems with Learned Policies
For many multiagent control problems, neural networks (NNs) have enabled promising new capabilities. However, many of these systems lack formal guarantees (e.g., collision avoidance, robustness), which prevents leveraging these advances in safety-critical settings. While there is recent work on formal verification of NN-controlled systems, most existing techniques cannot handle scenarios with more than one agent. To address this research gap, this paper presents a backward reachability-based ap…

N-MPC for Deep Neural Network-Based Collision Avoidance exploiting Depth Images
Martin Jacquet, Kostas Alexis
https://arxiv.org/abs/2402.13038 https://

N-MPC for Deep Neural Network-Based Collision Avoidance exploiting Depth Images
This paper introduces a Nonlinear Model Predictive Control (N-MPC) framework exploiting a Deep Neural Network for processing onboard-captured depth images for collision avoidance in trajectory-tracking tasks with UAVs. The network is trained on simulated depth images to output a collision score for queried 3D points within the sensor field of view. Then, this network is translated into an algebraic symbolic equation and included in the N-MPC, explicitly constraining predicted positions to be co…

Exploiting Over-The-Air Consensus for Collision Avoidance and Formation Control in Multi-Agent Systems
Michael Epp, Fabio Molinari, Joerg Raisch
https://arxiv.org/abs/2403.14386 <…

Exploiting Over-The-Air Consensus for Collision Avoidance and Formation Control in Multi-Agent Systems
This paper introduces a distributed control method for multi-agent robotic systems employing Over the Air Consensus (OTA-Consensus). Designed for agents with decoupled single-integrator dynamics, this approach aims at efficient formation achievement and collision avoidance. As a distinctive feature, it leverages OTA's ability to exploit interference in wireless channels, a property traditionally considered a drawback, thus enhancing communication efficiency among robots. An analytical proof of …

Spline Trajectory Tracking and Obstacle Avoidance for Mobile Agents via Convex Optimization
Akua Dickson, Christos G. Cassandras, Roberto Tron
https://arxiv.org/abs/2403.16900

Spline Trajectory Tracking and Obstacle Avoidance for Mobile Agents via Convex Optimization
We propose an output feedback control-based motion planning technique for agents to enable them to converge to a specified polynomial trajectory while imposing a set of safety constraints on our controller to avoid collisions within the free configuration space (polygonal environment). To achieve this, we 1) decompose our polygonal environment into different overlapping cells 2) write out our polynomial trajectories as the output of a reference dynamical system with given initial conditions 3) …

This https://arxiv.org/abs/2209.13628 has been replaced.
link: https://scholar.google.com/scholar?q=a

Unified Control Framework for Real-Time Interception and Obstacle Avoidance of Fast-Moving Objects with Diffusion Variational Autoencoder
Real-time interception of fast-moving objects by robotic arms in dynamic environments poses a formidable challenge due to the need for rapid reaction times, often within milliseconds, amidst dynamic obstacles. This paper introduces a unified control framework to address the above challenge by simultaneously intercepting dynamic objects and avoiding moving obstacles. Central to our approach is using diffusion-based variational autoencoder for motion planning to perform both object interception a…

This https://arxiv.org/abs/2310.02791 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

R-LGP: A Reachability-guided Logic-geometric Programming Framework for Optimal Task and Motion Planning on Mobile Manipulators
This paper presents an optimization-based solution to task and motion planning (TAMP) on mobile manipulators. Logic-geometric programming (LGP) has shown promising capabilities for optimally dealing with hybrid TAMP problems that involve abstract and geometric constraints. However, LGP does not scale well to high-dimensional systems (e.g. mobile manipulators) and can suffer from obstacle avoidance issues due to local minima. In this work, we extend LGP with a sampling-based reachability graph t…

Long-Term Human Trajectory Prediction using 3D Dynamic Scene Graphs
Nicolas Gorlo, Lukas Schmid, Luca Carlone
https://arxiv.org/abs/2405.00552 https://

Long-Term Human Trajectory Prediction using 3D Dynamic Scene Graphs
We present a novel approach for long-term human trajectory prediction, which is essential for long-horizon robot planning in human-populated environments. State-of-the-art human trajectory prediction methods are limited by their focus on collision avoidance and short-term planning, and their inability to model complex interactions of humans with the environment. In contrast, our approach overcomes these limitations by predicting sequences of human interactions with the environment and using thi…

This https://arxiv.org/abs/2401.09332 has been replaced.
link: https://scholar.google.com/scholar?q=a

Synergistic Reinforcement and Imitation Learning for Vision-driven Autonomous Flight of UAV Along River
Vision-driven autonomous flight and obstacle avoidance of Unmanned Aerial Vehicles (UAVs) along complex riverine environments for tasks like rescue and surveillance requires a robust control policy, which is yet difficult to obtain due to the shortage of trainable riverine environment simulators. To easily verify the vision-based navigation controller performance for the river following task before real-world deployment, we developed a trainable photo-realistic dynamics-free riverine simulation…

Deep Reinforcement Learning for Advanced Longitudinal Control and Collision Avoidance in High-Risk Driving Scenarios
Dianwei Chen, Yaobang Gong, Xianfeng Yang
https://arxiv.org/abs/2404.19087

This https://arxiv.org/abs/2303.15871 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Control Barrier Functions in Dynamic UAVs for Kinematic Obstacle Avoidance: A Collision Cone Approach
Unmanned aerial vehicles (UAVs), specifically quadrotors, have revolutionized various industries with their maneuverability and versatility, but their safe operation in dynamic environments heavily relies on effective collision avoidance techniques. This paper introduces a novel technique for safely navigating a quadrotor along a desired route while avoiding kinematic obstacles. We propose a new constraint formulation that employs control barrier functions (CBFs) and collision cones to ensure t…

Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning
Xi Lin, Yewei Huang, Fanfei Chen, Brendan Englot
https://arxiv.org/abs/2402.11799

Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning
Collision avoidance algorithms for Autonomous Surface Vehicles (ASV) that follow the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) have been proposed in recent years. However, it may be difficult and unsafe to follow COLREGs in congested waters, where multiple ASVs are navigating in the presence of static obstacles and strong currents, due to the complex interactions. To address this problem, we propose a decentralized multi-ASV collision avoidance polic…

Hybrid Feedback Control for Global and Optimal Safe Navigation
Ishak Cheniouni, Soulaimane Berkane, Abdelhamid Tayebi
https://arxiv.org/abs/2402.17038 http…

Hybrid Feedback Control for Global and Optimal Safe Navigation
We propose a hybrid feedback control strategy that safely steers a point-mass robot to a target location optimally from all initial conditions in the n-dimensional Euclidean space with a single spherical obstacle. The robot moves straight to the target when it has a clear line-of-sight to the target location. Otherwise, it engages in an optimal obstacle avoidance maneuver via the shortest path inside the cone enclosing the obstacle and having the robot's position as a vertex. The switching stra…

This https://arxiv.org/abs/2310.00273 has been replaced.
link: https://scholar.google.com/scholar?q=a

Safe Stabilizing Control for Polygonal Robots in Dynamic Elliptical Environments
This paper addresses the challenge of safe navigation for rigid-body mobile robots in dynamic environments. We introduce an analytic approach to compute the distance between a polygon and an ellipse, and employ it to construct a control barrier function (CBF) for safe control synthesis. Existing CBF design methods for mobile robot obstacle avoidance usually assume point or circular robots, preventing their applicability to more realistic robot body geometries. Our work enables CBF designs that …

This https://arxiv.org/abs/2402.01116 has been replaced.
link: https://scholar.google.com/scholar?q=a

Scalable Multi-modal Model Predictive Control via Duality-based Interaction Predictions
We propose a hierarchical architecture designed for scalable real-time Model Predictive Control (MPC) in complex, multi-modal traffic scenarios. This architecture comprises two key components: 1) RAID-Net, a novel attention-based Recurrent Neural Network that predicts relevant interactions along the MPC prediction horizon between the autonomous vehicle and the surrounding vehicles using Lagrangian duality, and 2) a reduced Stochastic MPC problem that eliminates irrelevant collision avoidance co…

This https://arxiv.org/abs/2402.17038 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Hybrid Feedback Control for Global and Optimal Safe Navigation
We propose a hybrid feedback control strategy that safely steers a point-mass robot to a target location optimally from all initial conditions in the n-dimensional Euclidean space with a single spherical obstacle. The robot moves straight to the target when it has a clear line-of-sight to the target location. Otherwise, it engages in an optimal obstacle avoidance maneuver via the shortest path inside the cone enclosing the obstacle and having the robot's position as a vertex. The switching stra…

This https://arxiv.org/abs/2309.01898 has been replaced.
link: https://scholar.google.com/scholar?q=a

Safe Legged Locomotion using Collision Cone Control Barrier Functions (C3BFs)
Legged robots exhibit significant potential across diverse applications, including but not limited to hazardous environment search and rescue missions and the exploration of unexplored regions both on Earth and in outer space. However, the successful navigation of these robots in dynamic environments heavily hinges on the implementation of efficient collision avoidance techniques. In this research paper, we employ Collision Cone Control Barrier Functions (C3BF) to ensure the secure movement of …

This https://arxiv.org/abs/2403.17392 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Natural-artificial hybrid swarm: Cyborg-insect group navigation in unknown obstructed soft terrain
Navigating multi-robot systems in complex terrains has always been a challenging task. This is due to the inherent limitations of traditional robots in collision avoidance, adaptation to unknown environments, and sustained energy efficiency. In order to overcome these limitations, this research proposes a solution by integrating living insects with miniature electronic controllers to enable robotic-like programmable control, and proposing a novel control algorithm for swarming. Although these c…

This https://arxiv.org/abs/2309.06494 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Non-smooth Control Barrier Functions for Stochastic Dynamical Systems
Uncertainties arising in various control systems, such as robots that are subject to unknown disturbances or environmental variations, pose significant challenges for ensuring system safety, such as collision avoidance. At the same time, safety specifications are getting more and more complex, e.g., by composing multiple safety objectives through Boolean operators resulting in non-smooth descriptions of safe sets. Control Barrier Functions (CBFs) have emerged as a control technique to provably …

Parking of Connected Automated Vehicles: Vehicle Control, Parking Assignment, and Multi-agent Simulation
Xu Shen, Yongkeun Choi, Alex Wong, Francesco Borrelli, Scott Moura, Soomin Woo
https://arxiv.org/abs/2402.14183

Parking of Connected Automated Vehicles: Vehicle Control, Parking Assignment, and Multi-agent Simulation
This paper introduces a novel approach to optimize the parking efficiency for fleets of Connected and Automated Vehicles (CAVs). We present a novel multi-vehicle parking simulator, equipped with hierarchical path planning and collision avoidance capabilities for individual CAVs. The simulator is designed to capture the key decision-making processes in parking, from low-level vehicle control to high-level parking assignment, and it enables the effective assessment of parking strategies for large…

This https://arxiv.org/abs/2209.01426 has been replaced.
link: https://scholar.google.com/scholar?q=a

Space Filling Curves for Coverage Path Planning with Online Obstacle Avoidance
The paper presents a strategy for robotic exploration problem using Space-Filling curves (SFC). The strategy plans a path that avoids unknown obstacles while ensuring complete coverage of the free space in region of interest. The region of interest is first tessellated, and the tiles/cells are connected using a SFC pattern. A robot follows the SFC to explore the entire area. However, obstacles can block the systematic movement of the robot. We overcome this problem by determining an alternate p…

A Control Barrier Function Composition Approach for Multi-Agent Systems in Marine Applications
Yujia Yang, Chris Manzie, Ye Pu
https://arxiv.org/abs/2403.14369

A Control Barrier Function Composition Approach for Multi-Agent Systems in Marine Applications
The agents within a multi-agent system (MAS) operating in marine environments often need to utilize task payloads and avoid collisions in coordination, necessitating adherence to a set of relative-pose constraints, which may include field-of-view, line-of-sight, collision-avoidance, and range constraints. A nominal controller designed for reference tracking may not guarantee the marine MAS stays safe w.r.t. these constraints. To modify the nominal input as one that enforces safety, we introduce…

This https://arxiv.org/abs/2402.01397 has been replaced.
link: https://scholar.google.com/scholar?q=a

A survey on robustness in trajectory prediction for autonomous vehicles
Autonomous vehicles rely on accurate trajectory prediction to inform decision-making processes related to navigation and collision avoidance. However, current trajectory prediction models show signs of overfitting, which may lead to unsafe or suboptimal behavior. To address these challenges, this paper presents a comprehensive framework that categorizes and assesses the definitions and strategies used in the literature on evaluating and improving the robustness of trajectory prediction models. …

Transformable Gaussian Reward Function for Socially-Aware Navigation with Deep Reinforcement Learning
Jinyeob Kim, Sumin Kang, Sungwoo Yang, Beomjoon Kim, Jargalbaatar Yura, Donghan Kim
https://arxiv.org/abs/2402.14569

Transformable Gaussian Reward Function for Socially-Aware Navigation with Deep Reinforcement Learning
Robot navigation has transitioned from prioritizing obstacle avoidance to adopting socially aware navigation strategies that accommodate human presence. As a result, the recognition of socially aware navigation within dynamic human-centric environments has gained prominence in the field of robotics. Although reinforcement learning technique has fostered the advancement of socially aware navigation, defining appropriate reward functions, especially in congested environments, has posed a signific…

Transformable Gaussian Reward Function for Socially-Aware Navigation with Deep Reinforcement Learning
Jinyeob Kim, Sumin Kang, Sungwoo Yang, Beomjoon Kim, Jargalbaatar Yura, Donghan Kim
https://arxiv.org/abs/2402.14569

Transformable Gaussian Reward Function for Socially-Aware Navigation with Deep Reinforcement Learning
Robot navigation has transitioned from prioritizing obstacle avoidance to adopting socially aware navigation strategies that accommodate human presence. As a result, the recognition of socially aware navigation within dynamic human-centric environments has gained prominence in the field of robotics. Although reinforcement learning technique has fostered the advancement of socially aware navigation, defining appropriate reward functions, especially in congested environments, has posed a signific…

This https://arxiv.org/abs/2402.01116 has been replaced.
link: https://scholar.google.com/scholar?q=a

Scalable Multi-modal Model Predictive Control via Duality-based Interaction Predictions
We propose a hierarchical architecture designed for scalable real-time Model Predictive Control (MPC) in complex, multi-modal traffic scenarios. This architecture comprises two key components: 1) RAID-Net, a novel attention-based Recurrent Neural Network that predicts relevant interactions along the MPC prediction horizon between the autonomous vehicle and the surrounding vehicles using Lagrangian duality, and 2) a reduced Stochastic MPC problem that eliminates irrelevant collision avoidance co…

Design and Flight Demonstration of a Quadrotor for Urban Mapping and Target Tracking Research
Collin Hague, Nick Kakavitsas, Jincheng Zhang, Chris Beam, Andrew Willis, Artur Wolek
https://arxiv.org/abs/2402.13195

Design and Flight Demonstration of a Quadrotor for Urban Mapping and Target Tracking Research
This paper describes the hardware design and flight demonstration of a small quadrotor with imaging sensors for urban mapping, hazard avoidance, and target tracking research. The vehicle is equipped with five cameras, including two pairs of fisheye stereo cameras that enable a nearly omnidirectional view and a two-axis gimbaled camera. An onboard NVIDIA Jetson Orin Nano computer running the Robot Operating System software is used for data collection. An autonomous tracking behavior was implemen…

This https://arxiv.org/abs/2312.09786 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Drones Guiding Drones: Cooperative Navigation of a Less-Equipped Micro Aerial Vehicle in Cluttered Environments
Reliable deployment of Unmanned Aerial Vehicles (UAVs) in cluttered unknown environments requires accurate sensors for Global Navigation Satellite System (GNSS)-denied localization and obstacle avoidance. Such a requirement limits the usage of cheap and micro-scale vehicles with constrained payload capacity if industrial-grade reliability and precision are required. This paper investigates the possibility of offloading the necessity to carry heavy sensors to another member of the UAV team while…

This https://arxiv.org/abs/2402.13195 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Design and Flight Demonstration of a Quadrotor for Urban Mapping and Target Tracking Research
This paper describes the hardware design and flight demonstration of a small quadrotor with imaging sensors for urban mapping, hazard avoidance, and target tracking research. The vehicle is equipped with five cameras, including two pairs of fisheye stereo cameras that enable a nearly omnidirectional view and a two-axis gimbaled camera. An onboard NVIDIA Jetson Orin Nano computer running the Robot Operating System software is used for data collection. An autonomous tracking behavior was implemen…

Reachability-based Trajectory Design via Exact Formulation of Implicit Neural Signed Distance Functions
Jonathan Michaux, Qingyi Chen, Challen Enninful Adu, Jinsun Liu, Ram Vasudevan
https://arxiv.org/abs/2403.12280

Reachability-based Trajectory Design via Exact Formulation of Implicit Neural Signed Distance Functions
Generating receding-horizon motion trajectories for autonomous vehicles in real-time while also providing safety guarantees is challenging. This is because a future trajectory needs to be planned before the previously computed trajectory is completely executed. This becomes even more difficult if the trajectory is required to satisfy continuous-time collision-avoidance constraints while accounting for a large number of obstacles. To address these challenges, this paper proposes a novel real-tim…