Tootfinder

Greenfields
When it's gone, it's gone.
The most objected to planning proposal in Bury's history - Manchester Evening News

The most objected to planning proposal in Bury's history
More than 1,000 comments have been officially registered on plans for 275 homes on green fields in Walshaw, with the vast majority objecting to the application

We Should Already Be Planning for Iran's Response (Mark Hertling/The Bulwark)
https://www.thebulwark.com/p/we-should-already-be-planning-for-iran-response-strike-bombing-nuclear-trump
http://www.memeorandum.com/250622/p63#a250622p63

Transporting a Dirac mass in a mean field planning problem
Pierre Cardaliaguet, Sebastian Munoz, Alessio Porretta
https://arxiv.org/abs/2506.16041 https://…

Transporting a Dirac mass in a mean field planning problem
We study a mean field planning problem in which the initial density is a Dirac mass. We show that there exists a unique solution which converges to a self-similar profile as time tends to $0$. We proceed by studying a continuous rescaling of the solution, and characterizing its behavior near the initial time through an appropriate Lyapunov functional.

Sheltering in a Bunker, Iran’s Supreme Leader Names Potential Successors
Ayatollah Ali Khamenei has not only picked replacements in his chain of military command in case they are killed in Israeli strikes,
he has also named three senior clerics to replace him should he, too, be slain.
Ayatollah Khamenei, 86, is aware that either Israel or the United States could try to assassinate him,
an end he would view as martyrdom, the officials said.
Given the possibility…

Ayatollah Ali Khamenei, Planning for His Possible Assassination, Picks Successors
Ayatollah Ali Khamenei has not only picked replacements in his chain of military command in case they are killed in Israeli strikes, he has also named three senior clerics to replace him should he, too, be slain.

Iran is arguably more democratic than the US today, in this very narrow way… https://fed.brid.gy/r/https://bsky.app/profile/did:plc:gvda6fem6r7selm4gzjjww4a/post/3ls764pktnk2e

The Anarchist Cookbook, 2025 Edition:
Recent US political violence aided by DIY murder tradecraft available on internet;
People locators, 3D weapon blueprints, tactical planning – all accessible on the web for potential attackers or terrorists
https://www.theguardian…

When I heard the news that the US bombed Iran. I had to remind myself of what I witnessed this past week - millions of people turned out for #NoKings. Three retiree women in a coffee shop planning their resistance. And these fiber art designs in Lanesboro, MN I saw this weekend. (Shout out to Driftless Fiber Arts) Not the kind of town where you'd expect to see resistance art or pride parad…

Join Radu Pop and Pietro Mele at Berlin Buzzwords as they discuss building an extensible hybrid search solution with Elasticsearch. They will cover functional modeling, cluster architecture, and practical insights on managing billions of vectors in real-world scenarios. Radu and Pietro will also address hybrid reranking challenges and the limitations of standard fusion techniques, explaining their innovative approach.
Learn more:

This The Beaverton article is so funny, and not funny.
https://thebeaverton.com/2025/06/canadians-travelling-to-the-us-advised-to-not-fucking-do-that/

Canadians travelling to the US advised to not fucking do that
OTTAWA - Canadians thinking of planning a trip to the United States are being advised by the Government of Canada to perhaps consider going anywhere else on the entire fucking planet for their summer vacations. 

Microsoft is planning another round of redundancies, with a significant number of sales jobs to go as part of AI push, media reports say.
https://www.computing.co.uk/news/2025/more-jobs-to-go-at-microsoft-next-month-report

More jobs to go at Microsoft next month, report
Microsoft is planning another round of redundancies, with a significant number of sales jobs to go, media reports say.

Sources: Meta tried to buy Safe Superintelligence earlier this year; Zuckerberg moved to recruit SSI CEO Daniel Gross after Ilya Sutskever rebuffed the offer (Kate Rooney/CNBC)
https://www.cnbc.com/2025/06/19/meta-tried-to-buy-s…

Meta tried to buy Ilya Sutskever's $32 billion AI startup, but is now planning to hire its CEO
Meta plans to hire Safe Superintelligence CEO Daniel Gross and former GitHub Nat Friedman to beef up the company's AI team, according to sources.

Two different takes on the potential of AI for cataloguing in 'Catalogue and Index'
'Augmenting cataloguers' https://journals.cilip.org.uk/catalogue-and-index/article/view/750
'Smart enough to mislead'

I had the BEST time recording with @catherine_ashton_critical of Critical Info this morning! (Not, I must say, in an Oodie but Remy needed a walk 😉 ) We talked about end of life doulas, advance planning, grief, inclusive death care, and why a pet's death can be just as devastating as a human's.
Catherine's work is extraordinary and high-calibre, I encourage you to follow her if you don't already.
What are your weekend plans??!

Refugee Makes History Becoming British Ambassador: ‘Mom Was Worried I Wasn’t English Enough’ https://www.goodnewsnetwork.org/first-ever-refugee-appointed-as-a-british-ambassador-reflects-on-…

Refugee Makes History Becoming British Ambassador: 'Mom Was Worried I Wasn't English Enough'
He admitted his mother was nervous when she first heard he was planning to join the Foreign Office, equivalent of the US State Department.

Small towns are growing fast across Ghana—but environmental planning isn't keeping up #Africa

Small towns are growing fast across Ghana—but environmental planning isn't keeping up
Africa's urban future will be shaped not only by large cities and capitals but also by its many small and medium-sized towns.

Leo Varadkar, who stood down as taoiseach in April 2024,
said he did not think a date should be fixed for an Irish unity referendum
as nationalists did not yet have the numbers to win.
But he said planning for a united Ireland should take place.
"I don't think a united Ireland is inevitable, I think it's something that we have to work towards," he said.
"But I think there are a lot of factors that would suggest that we're on that traje…

Leo Varadkar says Nigel Farage as PM would move Irish unity 'centre stage'
The former Irish prime minister says planning should take place for the possibility of Irish unification.

Swarm-STL: A Framework for Motion Planning in Large-Scale, Multi-Swarm Systems
Shiyu Cheng, Luyao Niu, Bhaskar Ramasubramanian, Andrew Clark, Radha Poovendran
https://arxiv.org/abs/2506.14749

Swarm-STL: A Framework for Motion Planning in Large-Scale, Multi-Swarm Systems
In multi-agent systems, signal temporal logic (STL) is widely used for path planning to accomplish complex objectives with formal safety guarantees. However, as the number of agents increases, existing approaches encounter significant computational challenges. Recognizing that many complex tasks require cooperation among multiple agents, we propose swarm STL specifications to describe the collective tasks that need to be achieved by a team of agents. Next, we address the motion planning problem…

Robust Optimal Task Planning to Maximize Battery Life
Jiachen Li, Chu Jian, Feiyang Zhao, Shihao Li, Wei Li, Dongmei Chen
https://arxiv.org/abs/2506.11264 …

Robust Optimal Task Planning to Maximize Battery Life
This paper proposes a control-oriented optimization platform for autonomous mobile robots (AMRs), focusing on extending battery life while ensuring task completion. The requirement of fast AMR task planning while maintaining minimum battery state of charge, thus maximizing the battery life, renders a bilinear optimization problem. McCormick envelop technique is proposed to linearize the bilinear term. A novel planning algorithm with relaxed constraints is also developed to handle parameter unce…

Optimal Navigation in Microfluidics via the Optimization of a Discrete Loss
Petr Karnakov, Lucas Amoudruz, Petros Koumoutsakos
https://arxiv.org/abs/2506.15902

Optimal Navigation in Microfluidics via the Optimization of a Discrete Loss
Optimal path planning and control of microscopic devices navigating in fluid environments is essential for applications ranging from targeted drug delivery to environmental monitoring. These tasks are challenging due to the complexity of microdevice-flow interactions. We introduce a closed-loop control method that optimizes a discrete loss (ODIL) in terms of dynamics and path objectives. In comparison with reinforcement learning, ODIL is more robust, up to three orders faster, and excels in hig…

Towards Emergency Scenarios: An Integrated Decision-making Framework of Multi-lane Platoon Reorganization
Aijing Kong, Chengkai Xu, Xian Wu, Xinbo Chen, Peng Hang
https://arxiv.org/abs/2506.16311

Towards Emergency Scenarios: An Integrated Decision-making Framework of Multi-lane Platoon Reorganization
To enhance the ability for vehicle platoons to respond to emergency scenarios, a platoon distribution reorganization decision-making framework is proposed. This framework contains platoon distribution layer, vehicle cooperative decision-making layer and vehicle planning and control layer. Firstly, a reinforcement-learning-based platoon distribution model is presented, where a risk potential field is established to quantitatively assess driving risks, and a reward function tailored to the platoo…

Linear Planar 3-SAT and Its Applications in Planning
Victorien Desbois, Ocan Sankur, Fran\c{c}ois Schwarzentruber
https://arxiv.org/abs/2506.14713 https://…

Linear Planar 3-SAT and Its Applications in Planning
Several fragments of the satisfiability problem have been studied in the literature. Among these, Linear 3-SAT is a satisfaction problem in which each clause (viewed as a set of literals) intersects with at most one other clause; moreover, any pair of clauses have at most one literal in common. Planar 3-SAT is a fragment which requires that the so-called variable-clause graph is planar. Both fragments are NP-complete and have applications in encoding NP-hard planning problems. In this paper, we…

Advanced approach for Agile/Scrum Process: RetroAI
Maria Spichkova, Kevin Iwan, Madeleine Zwart, Hina Lee, Yuwon Yoon, Xiaohan Qin
https://arxiv.org/abs/2506.15172

Advanced approach for Agile/Scrum Process: RetroAI++
In Agile/Scrum software development, sprint planning and retrospective analysis are the key elements of project management. The aim of our work is to support software developers in these activities. In this paper, we present our prototype tool RetroAI++, based on emerging intelligent technologies. In our RetroAI++ prototype, we aim to automate and refine the practical application of Agile/Scrum processes within Sprint Planning and Retrospectives. Leveraging AI insights, our prototype aims to au…

Just scrolling through the "Tree Preservation Orders" MHCLG has published geo-data for.
https://www.planning.data.gov.uk/dataset/tree

Digital Transformation of Urban Planning in Australia: Influencing Factors and Key Challenges
Soheil Sabri, Sherah Kurnia
https://arxiv.org/abs/2506.13333 …

Digital Transformation of Urban Planning in Australia: Influencing Factors and Key Challenges
Over the past two decades, several governments in developing and developed countries have started their journey toward digital transformation. However, the pace and maturity of digital technologies and strategies are different between public services. Current literature indicates that research on the digital transformation of urban planning is still developing. Therefore, the aim of this study is to understand the influencing factors and key challenges for the digital transformation of urban pl…

https://techcrunch.com/2025/04/05/doge-reportedly-planning-a-hackathon-to-build-mega-api-for-irs-data/

Ars Technica author Ashley Belanger presents both consumer rights advocacy group Public Citizen's position against the use of AI in toys, and toy maker Mattel's and Open AI's. Public Citizen's tone is baselessly alarmist, given that "Both companies [have] emphasized that safety, privacy, and age-appropriateness would be front of mind in designing Mattel's AI products."
"Toy-maker Mattel accused of planning 'reckless' AI social experiment on k…

🌎 🌍 New agreement between GÉANT and EXA Infrastructure to deliver terabit expansion of R&E connectivity between #Europe and #NorthAmerica.
This strategic investment, procured under the GN5-IC1 project and planned in coordination with our community, with ESnet and with the ANA collaboration, …

GÉANT and EXA Infrastructure announce IRU agreement for terabit expansion of transatlantic R&E connectivity between Europe and North America | GÉANT CONNECT Online
GÉANT and digital infrastructure provider EXA Infrastructure are excited to announce the signature of an historical long-term agreement to deliver a major expansion of the transatlantic connectivity dedicated to Research and Education (R&E) collaboration between Europe and North America. Procured under GN5-IC1, the ambitious project planning and implementing GÉANT’s intercontinental connectivity investments, the new Indefeasible

Neun sekunden warten und dann gephished werden.
#phishing

Neun sekunden warten und dann gephished werden.
#phishing

Not now scientists planning to investigate strange signals coming from deep beneath Antarctica. https://journa.host/@mathewi/114699252029118307

Southern California Edison
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We understand that planning around outages is inconvenient. Thanks for your patience as we work to keep our communities safe.
If your power is off, please call 1-800-611-1911 or visit
sce.com/psps.
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How attention simplifies mental representations for planning
Jason da Silva Castanheira, Nicholas Shea, Stephen M. Fleming
https://arxiv.org/abs/2506.09520

How attention simplifies mental representations for planning
Human planning is efficient -- it frugally deploys limited cognitive resources to accomplish difficult tasks -- and flexible -- adapting to novel problems and environments. Computational approaches suggest that people construct simplified mental representations of their environment, balancing the complexity of a task representation with its utility. These models imply a nested optimisation in which planning shapes perception, and perception shapes planning -- but the perceptual and attentional …

FindingDory: A Benchmark to Evaluate Memory in Embodied Agents
Karmesh Yadav, Yusuf Ali, Gunshi Gupta, Yarin Gal, Zsolt Kira
https://arxiv.org/abs/2506.15635

FindingDory: A Benchmark to Evaluate Memory in Embodied Agents
Large vision-language models have recently demonstrated impressive performance in planning and control tasks, driving interest in their application to real-world robotics. However, deploying these models for reasoning in embodied contexts is limited by their ability to incorporate long-term experience collected across multiple days and represented by vast collections of images. Current VLMs typically struggle to process more than a few hundred images concurrently, highlighting the need for more…

ChatGPT didn't object to putting a red nose on the dog or painting the rabbits green, but at least it didn't suggest I use staplers on the mice.
#scrooged #chatgpt

Joint UAV Trajectory Planning and LEO Satellite Selection for Data Offloading in Space-Air-Ground Integrated Networks
Boran Wang, Ziye Jia, Can Cui, Qihui Wu
https://arxiv.org/abs/2506.12750

Joint UAV Trajectory Planning and LEO Satellite Selection for Data Offloading in Space-Air-Ground Integrated Networks
With the development of low earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs), the space-air-ground integrated network (SAGIN) becomes a major trend in the next-generation networks. However, due to the instability of heterogeneous communication and time-varying characteristics of SAGIN, it is challenging to meet the remote Internet of Things (IoT) demands for data collection and offloading. In this paper, we investigate a two-phase hierarchical data uplink model in SAGIN. Specifi…

A new guide focusing on renewables-based electrification of road transport by #IRENA, embedded into wider sustainable transport planning (e.g. prioritize public transport). Efficiency of electrification renewables smart charging & V2G key to enable system-wide benefits

I do not understand why folks aren’t mildly freaking out on the extended forecasts for #NYC
Seriously #HeatWave
To have five days (!!!5 days !!!) of over 100degF
Check on your neighbors.
Prepare now for no or low power. Get your spritzer and battery powered electric fans.
We will get through this together. But it will be easier with a little bit of planning.
Where is your NYC cooling center??
https://finder.nyc.gov/coolingcenters/

#Agile Development was invented in the Soviet Union.

3D Skin Segmentation Methods in Medical Imaging: A Comparison
Martina Paccini, Giuseppe Patan\`e
https://arxiv.org/abs/2506.11852 https://

3D Skin Segmentation Methods in Medical Imaging: A Comparison
Automatic segmentation of anatomical structures is critical in medical image analysis, aiding diagnostics and treatment planning. Skin segmentation plays a key role in registering and visualising multimodal imaging data. 3D skin segmentation enables applications in personalised medicine, surgical planning, and remote monitoring, offering realistic patient models for treatment simulation, procedural visualisation, and continuous condition tracking. This paper analyses and compares algorithmic an…

Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning
Mohammadamin Moradi, Runyu Jiang, Yingzi Liu, Malvern Madondo, Tianming Wu, James J. Sohn, Xiaofeng Yang, Yasmin Hasan, Zhen Tian
https://arxiv.org/abs/2506.11957…

Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning
High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual treatment planning expertise. The objective of this study is to develop a fully automated HDR brachytherapy planning framework that integrates reinforcement learning (RL) and dose-based optimization to generate clinically acceptable treatment plans with improved consistency and efficiency. We propose a hierarchical two-stage autoplanning framework.…

Damn; I quite liked the ammonia story;
https://www.hydrogeninsight.com/production/air-products-shelves-2bn-plan-to-import-green-ammonia-to-uk-and-crack-it-back-to-hydrogen/2-1-1833888

Air Products shelves £2bn plan to import green ammonia to UK and crack it back to hydrogen
The industrial gases firm had received planning permission for the Immingham terminal earlier this year, but blames lack of policy support for its decision

Sooo... I was in town and this guy looked at me funny. I'm pretty sure he was planning something.
So I shot him dead.
What do you mean I was the aggressor? What do you mean 'murder is illegal, you striking first is not self defence?'
He was blatantly shifty.
^ THE ENTIRE WESTERN MEDIA TODAY

@… Yeah, ordered it months ago, it was a gift from my partner. 😊
I’m planning on mostly playing Switch 1 games. Part of the reason I didn’t get the first one is that for the first couple of years, it was lacking in games, and after that, it felt like a lot of money for such an underpowered device.
Not enjoying the game prices though.

Discovering Temporal Structure: An Overview of Hierarchical Reinforcement Learning
Martin Klissarov, Akhil Bagaria, Ziyan Luo, George Konidaris, Doina Precup, Marlos C. Machado
https://arxiv.org/abs/2506.14045

Discovering Temporal Structure: An Overview of Hierarchical Reinforcement Learning
Developing agents capable of exploring, planning and learning in complex open-ended environments is a grand challenge in artificial intelligence (AI). Hierarchical reinforcement learning (HRL) offers a promising solution to this challenge by discovering and exploiting the temporal structure within a stream of experience. The strong appeal of the HRL framework has led to a rich and diverse body of literature attempting to discover a useful structure. However, it is still not clear how one might …

Canadians travelling to the US advised to not fucking do that
https://www.thebeaverton.com/2025/06/canadians-travelling-to-the-us-advised-to-not-fucking-do-that/

Canadians travelling to the US advised to not fucking do that
OTTAWA - Canadians thinking of planning a trip to the United States are being advised by the Government of Canada to perhaps consider going anywhere else on the entire fucking planet for their summer vacations. 

Towards Perception-based Collision Avoidance for UAVs when Guiding the Visually Impaired
Suman Raj, Swapnil Padhi, Ruchi Bhoot, Prince Modi, Yogesh Simmhan
https://arxiv.org/abs/2506.14857

Towards Perception-based Collision Avoidance for UAVs when Guiding the Visually Impaired
Autonomous navigation by drones using onboard sensors combined with machine learning and computer vision algorithms is impacting a number of domains, including agriculture, logistics, and disaster management. In this paper, we examine the use of drones for assisting visually impaired people (VIPs) in navigating through outdoor urban environments. Specifically, we present a perception-based path planning system for local planning around the neighborhood of the VIP, integrated with a global plann…

BESS Participation Planning for Provision of Grid Services in Energy and Regulation Markets
Zeenat Hameed, Chresten Traeholt
https://arxiv.org/abs/2506.08472

BESS Participation Planning for Provision of Grid Services in Energy and Regulation Markets
This paper presents a stochastic optimization model for planning the participation of battery energy storage systems (BESSs) in energy and regulation markets. The proposed model quantifies and compares the business value of single and multi-market BESS services by accounting for their bid submission and acceptance procedures, pricing mechanisms and revenue streams, and penalty payments and degradation costs. By modelling the price uncertainties using market price scenarios (MPSs) and considerin…

Sources: Microsoft plans to announce thousands of job cuts, particularly in sales, early next month after the end of its fiscal year (Bloomberg)
https://www.bloomberg.com/news/articles/2025-06-18/microsoft-planning…

Constrained Diffusers for Safe Planning and Control
Jichen Zhang, Liqun Zhao, Antonis Papachristodoulou, Jack Umenberger
https://arxiv.org/abs/2506.12544 h…

Constrained Diffusers for Safe Planning and Control
Diffusion models have shown remarkable potential in planning and control tasks due to their ability to represent multimodal distributions over actions and trajectories. However, ensuring safety under constraints remains a critical challenge for diffusion models. This paper proposes Constrained Diffusers, a novel framework that incorporates constraints into pre-trained diffusion models without retraining or architectural modifications. Inspired by constrained optimization, we apply a constrained…

Poultry megafarm in Shropshire halted over river pollution concerns https://www.theguardian.com/environment/2025/jun/17/poultry-megafarm-in-shropshire-halted-over-river-pollution-concerns

Rapid cardiac activation prediction for cardiac resynchronization therapy planning using geometric deep learning
Ehsan Naghavi, Haifeng Wang, Vahid Ziaei Rad, Julius Guccione, Ghassan Kassab, Vishnu Boddeti, Seungik Baek, Lik-Chuan Lee
https://arxiv.org/abs/2506.08987

Rapid cardiac activation prediction for cardiac resynchronization therapy planning using geometric deep learning
Cardiac resynchronization therapy (CRT) is a common intervention for patients with dyssynchronous heart failure, yet approximately one-third of recipients fail to respond due to suboptimal lead placement. Identifying optimal pacing sites remains challenging, largely due to patient-specific anatomical variability and the limitations of current individualized planning strategies. In a step towards constructing an in-silico approach to help address this issue, we develop two geometric deep learnin…

Reminder: public protest is about visibility, not hiding. The power comes from people being willing to be visible, put their time on the line, and if needed, their bodies.
If you're going to start shit, maybe just ... don't. Direct action of the illegal sort requires careful planning and a tactical and strategic plan for why it will win. It happens sometimes, but it's not the mode, it's not the mode of the No Kings protests. This is a popular, public demonstration of outrage. It's legal (for now, and I hope, ever).
Yes, the police may try to kettle protesters and then trap them into curfew violations in places that have curfews. Masks won't save us from that where it happens. Just running the system with competent representation (and enough bodies to make it A Problem for the system) will.
We don't all need to be masked vigilantes at protests, and in a lot of cases, we need to be worried about the people masking up and starting shit. Remember that this is our opponents current tactic: masked, violent attacks. Don't look like them.

Minneapolis and Saint Paul are finally launching this BRT line that was already in the planning phase when I last visited in ... 2019.
Good, but if it's gonna take that long, maybe agencies should just incrementally upgrade the buses that exist instead of these big fancy unicorn "BRT" projects?
https://

Creating Buzz for the B Line
The Twin Cities’ newest BRT line is an attractive option that could turn more people into transit users — if they know about it!

“Discord just made an announcement…” where’s an official link then?
“Feel free to copy and paste to other servers.”
No, I do not think I will.
I’ve already seen this song and dance before. Last time it was about VRChat rippers and crashers supposedly planning to do mass raids on a particular day. So far as I have experienced and heard, nothing came of it.
I don’t appreciate the unverified @everyone spam.

O.k., more screencaps from Michael Zeiler's #SolarEclipse Conference talk: stills from animations of the umbra moving over Spain in 2026 and 2027, setting the stage for tomorrow when most of the sessions will deal with future eclipses and planning. This summer a new website, EclipseAtlas.com (not up yet) will collect all old and new eclipse maps material. 9/n

NFL news roundup: Dolphins CB Jalen Ramsey not planning on attending mandatory minicamp as sides continue to work towards trade https://www.nfl.com/news/nfl-news-roundup-latest-league-updates-from-sunday-june-8

"The cult of goal-setting thrives in this illusion. It converts uncertainty into an illusion of progress. It demands specificity in exchange for comfort. And it replaces self-trust with the performance of future-planning."
(Original title: Smart People Don't Chase Goals; They Create Limits)

Smart People Don't Chase Goals; They Create Limits
A few years ago, I sat across from a friend at a late dinner. He was telling me about his new promotion, the big title, the bonus, the corner office. I remember watching his face as he described it. He looked like someone describing a story he’d once believed

Procedures for Constraining Robotic Fiber Positioning for Highly Multiplexed Spectroscopic Surveys: The Case of FPS for SDSS-V
Ilija Medan, Tom Dwelly, Kevin R. Covey, Eleonora Zari, Michael R. Blanton, Joleen K. Carlberg, S. Drew Chojnowski, Alexander Ji, Yue Shen, John Donor, Jos\'e S\'anchez-Gallego, Sean Morrison, H\'ector J. Ibarra-Medel, Conor Sayres, Keivan G. Stassun

Procedures for Constraining Robotic Fiber Positioning for Highly Multiplexed Spectroscopic Surveys: The Case of FPS for SDSS-V
One crucial aspect of planning any large scale astronomical survey is constructing an observing strategy that maximizes reduced data quality. This is especially important for surveys that are rather heterogeneous and broad-ranging in their science goals. The Sloan Digital Sky Survey V (SDSS-V), which now utilizes the Focal Plane System (FPS) to robotically place fibers that feed the spectrographs, certainly meets these criteria. The addition of the FPS facilities an increase in survey efficienc…

Gondola: Grounded Vision Language Planning for Generalizable Robotic Manipulation
Shizhe Chen, Ricardo Garcia, Paul Pacaud, Cordelia Schmid
https://arxiv.org/abs/2506.11261

Gondola: Grounded Vision Language Planning for Generalizable Robotic Manipulation
Robotic manipulation faces a significant challenge in generalizing across unseen objects, environments and tasks specified by diverse language instructions. To improve generalization capabilities, recent research has incorporated large language models (LLMs) for planning and action execution. While promising, these methods often fall short in generating grounded plans in visual environments. Although efforts have been made to perform visual instructional tuning on LLMs for robotic manipulation,…

Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation
Alex C. Newkirk, Jared Fernandez, Jonathan Koomey, Imran Latif, Emma Strubell, Arman Shehabi, Constantine Samaras
https://arxiv.org/abs/2506.14551

Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation
As AI's energy demand continues to grow, it is critical to enhance the understanding of characteristics of this demand, to improve grid infrastructure planning and environmental assessment. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-GPU H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design pow…

Nearly 100 House Democrats urge RFK Jr. to restore millions in family planning grants (Nathaniel Weixel/The Hill)
https://thehill.com/policy/healthcare/5337240-lawmakers-robert-f-kennedy-jr-restoration-family-planning-grants/
http://www.memeorandum.com/250606/p107#a250606p107

Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Xinglei Wang, Tao Cheng, Stephen Law, Zichao Zeng, Ilya Ilyankou, Junyuan Liu, Lu Yin, Weiming Huang, Natchapon Jongwiriyanurak
https://arxiv.org/abs/2506.14070…

Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Predicting individuals' next locations is a core task in human mobility modelling, with wide-ranging implications for urban planning, transportation, public policy and personalised mobility services. Traditional approaches largely depend on location embeddings learned from historical mobility patterns, limiting their ability to encode explicit spatial information, integrate rich urban semantic context, and accommodate previously unseen locations. To address these challenges, we explore the appl…

Recursive Variational Autoencoders for 3D Blood Vessel Generative Modeling
Paula Feldman, Miguel Fainstein, Viviana Siless, Claudio Delrieux, Emmanuel Iarussi
https://arxiv.org/abs/2506.14914

Recursive Variational Autoencoders for 3D Blood Vessel Generative Modeling
Anatomical trees play an important role in clinical diagnosis and treatment planning. Yet, accurately representing these structures poses significant challenges owing to their intricate and varied topology and geometry. Most existing methods to synthesize vasculature are rule based, and despite providing some degree of control and variation in the structures produced, they fail to capture the diversity and complexity of actual anatomical data. We developed a Recursive variational Neural Network…

CDP: Towards Robust Autoregressive Visuomotor Policy Learning via Causal Diffusion
Jiahua Ma, Yiran Qin, Yixiong Li, Xuanqi Liao, Yulan Guo, Ruimao Zhang
https://arxiv.org/abs/2506.14769

CDP: Towards Robust Autoregressive Visuomotor Policy Learning via Causal Diffusion
Diffusion Policy (DP) enables robots to learn complex behaviors by imitating expert demonstrations through action diffusion. However, in practical applications, hardware limitations often degrade data quality, while real-time constraints restrict model inference to instantaneous state and scene observations. These limitations seriously reduce the efficacy of learning from expert demonstrations, resulting in failures in object localization, grasp planning, and long-horizon task execution. To add…

Happy Pride! Everyone deserves dignity and respect at every stage of their life - including end of life. Help your loved ones and community celebrate you properly and appropriately by doing all your advance planning now -just think of how hard you'll party when it's done 🎉🌈
Got questions? I'm here to help and I am an ally and safe space for everyone in the LGBTIQA community and the kink community.

Deceptive Path Planning: A Bayesian Game Approach
Violetta Rostobaya, James Berneburg, Yue Guan, Michael Dorothy, Daigo Shishika
https://arxiv.org/abs/2506.13650

Deceptive Path Planning: A Bayesian Game Approach
This paper investigates how an autonomous agent can transmit information through its motion in an adversarial setting. We consider scenarios where an agent must reach its goal while deceiving an intelligent observer about its destination. We model this interaction as a dynamic Bayesian game between a mobile Attacker with a privately known goal and a Defender who infers the Attacker's intent to allocate defensive resources effectively. We use Perfect Bayesian Nash Equilibrium (PBNE) as our solut…

Dynamic Less-Than-Truckload Transportation Planning in Hyperconnected Hub Networks with Multi-Carrier Operations
Tiankuo Zhang, Jingze Li, Benoit Montreuil
https://arxiv.org/abs/2506.10290

Dynamic Less-Than-Truckload Transportation Planning in Hyperconnected Hub Networks with Multi-Carrier Operations
Less-than-truckload (LTL) shipment is vital in modern freight transportation yet is in dire need of more efficient usage of resources, higher service responsiveness and velocity, lower overall shipping cost across all parties, and better quality of life for the drivers. The industry is currently highly fragmented, with numerous small to medium-sized LTL carriers typically operating within dedicated regions or corridors, mostly disconnected from each other. This paper investigates the large-scal…

A Digital Twin Framework for Adaptive Treatment Planning in Radiotherapy
Chih-Wei Chang, Sri Akkineni, Mingzhe Hu, Keyur D. Shah, Jun Zhou, Xiaofeng Yang
https://arxiv.org/abs/2506.14701

A Digital Twin Framework for Adaptive Treatment Planning in Radiotherapy
This study aims to develop and evaluate a digital twin (DT) framework to enhance adaptive proton therapy for prostate stereotactic body radiotherapy (SBRT), focusing on improving treatment precision for dominant intraprostatic lesions (DILs) while minimizing organ-at-risk (OAR) toxicity. We propose a decision-theoretic (DT) framework combining deep learning (DL)-based deformable image registration (DIR) with a prior treatment database to generate synthetic CTs (sCTs) for predicting interfractio…

Re4MPC: Reactive Nonlinear MPC for Multi-model Motion Planning via Deep Reinforcement Learning
Ne\c{s}et \"Unver Akmandor, Sarvesh Prajapati, Mark Zolotas, Ta\c{s}k{\i}n Pad{\i}r
https://arxiv.org/abs/2506.08344

Re4MPC: Reactive Nonlinear MPC for Multi-model Motion Planning via Deep Reinforcement Learning
Traditional motion planning methods for robots with many degrees-of-freedom, such as mobile manipulators, are often computationally prohibitive for real-world settings. In this paper, we propose a novel multi-model motion planning pipeline, termed Re4MPC, which computes trajectories using Nonlinear Model Predictive Control (NMPC). Re4MPC generates trajectories in a computationally efficient manner by reactively selecting the model, cost, and constraints of the NMPC problem depending on the comp…

Niners LT Trent Williams on goal of playing till he’s 40: ‘Not going to retire with something left on the table’ https://www.nfl.com/news/niners-lt-trent-williams-on-goal-of-playing-till-he-s-40-not-g…

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes
Jiahao Qiu, Xinzhe Juan, Yimin Wang, Ling Yang, Xuan Qi, Tongcheng Zhang, Jiacheng Guo, Yifu Lu, Zixin Yao, Hongru Wang, Shilong Liu, Xun Jiang, Liu Leqi, Mengdi Wang
https://arxiv.org/abs/2506.14728

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes
While knowledge distillation has become a mature field for compressing large language models (LLMs) into smaller ones by aligning their outputs or internal representations, the distillation of LLM-based agents, which involve planning, memory, and tool use, remains relatively underexplored. Existing agent distillation methods typically replay full teacher trajectories or imitate step-by-step teacher tool usage, but they often struggle to train student agents to dynamically plan and act in novel …

PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly
Liang Ma, Jiajun Wen, Min Lin, Rongtao Xu, Xiwen Liang, Bingqian Lin, Jun Ma, Yongxin Wang, Ziming Wei, Haokun Lin, Mingfei Han, Meng Cao, Bokui Chen, Ivan Laptev, Xiaodan Liang
https://arxiv.org/abs/2506.08708

PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly
While vision-language models (VLMs) have demonstrated promising capabilities in reasoning and planning for embodied agents, their ability to comprehend physical phenomena, particularly within structured 3D environments, remains severely limited. To close this gap, we introduce PhyBlock, a progressive benchmark designed to assess VLMs on physical understanding and planning through robotic 3D block assembly tasks. PhyBlock integrates a novel four-level cognitive hierarchy assembly task alongside …

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification
Zahid Ullah, Jihie Kim
https://arxiv.org/abs/2506.12363 …

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification
Accurate brain tumor classification is crucial in medical imaging to ensure reliable diagnosis and effective treatment planning. This study introduces a novel double ensembling framework that synergistically combines pre-trained deep learning (DL) models for feature extraction with optimized machine learning (ML) classifiers for robust classification. The framework incorporates comprehensive preprocessing and data augmentation of brain magnetic resonance images (MRI), followed by deep feature e…

Linear, which makes software development and project planning tools that rival Atlassian's Jira, raised an $82M Series C led by Accel, valuing it at $1.25B (Anna Tong/Reuters)
https://www.reuters.com/business/atlassian

Sampling-Based Planning Under STL Specifications: A Forward Invariance Approach
Gregorio Marchesini, Siyuan Liu, Lars Lindemann, Dimos V. Dimarogonas
https://arxiv.org/abs/2506.10739

Sampling-Based Planning Under STL Specifications: A Forward Invariance Approach
We propose a variant of the Rapidly Exploring Random Tree Star (RRT$^{\star}$) algorithm to synthesize trajectories satisfying a given spatio-temporal specification expressed in a fragment of Signal Temporal Logic (STL) for linear systems. Previous approaches for planning trajectories under STL specifications using sampling-based methods leverage either mixed-integer or non-smooth optimization techniques, with poor scalability in the horizon and complexity of the task. We adopt instead a contro…

From Theory to Practice: Advancing Multi-Robot Path Planning Algorithms and Applications
Teng Guo
https://arxiv.org/abs/2506.09914 https://

From Theory to Practice: Advancing Multi-Robot Path Planning Algorithms and Applications
The labeled MRPP (Multi-Robot Path Planning) problem involves routing robots from start to goal configurations efficiently while avoiding collisions. Despite progress in solution quality and runtime, its complexity and industrial relevance continue to drive research. This dissertation introduces scalable MRPP methods with provable guarantees and practical heuristics. First, we study dense MRPP on 2D grids, relevant to warehouse and parcel systems. We propose the Rubik Table method, achieving …

The Washington Post could soon allow non-professional writers to submit opinion columns using an AI writing coach known as Ember,
according to a report from The New York Times.
The move is reportedly part of a broader initiative to open the paper to outside opinion pieces, including from other publications, Substack writers, and amateur columnists.
Sources tell the Times that Ember “could automate several functions normally provided by human editors,”
including by offe…

The Washington Post is planning to let amateur writers submit columns — with the help of AI
The Washington Post is planning a new initiative that will allow non-professional writers to submit opinion pieces using an AI-powered writing coach, called Ember, according to The New York Times.

This https://arxiv.org/abs/2503.22030 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Bayesian Inferential Motion Planning Using Heavy-Tailed Distributions
Robots rely on motion planning to navigate safely and efficiently while performing various tasks. In this paper, we investigate motion planning through Bayesian inference, where motion plans are inferred based on planning objectives and constraints. However, existing Bayesian motion planning methods often struggle to explore low-probability regions of the planning space, where high-quality plans may reside. To address this limitation, we propose the use of heavy-tailed distributions -- specific…

Exploiting Euclidean Distance Field Properties for Fast and Safe 3D planning with a modified Lazy Theta*
Jose A. Cobano, L. Merino, F. Caballero
https://arxiv.org/abs/2505.24024

Exploiting Euclidean Distance Field Properties for Fast and Safe 3D planning with a modified Lazy Theta*
Graph search planners have been widely used for 3D path planning in the literature, and Euclidean Distance Fields (EDFs) are increasingly being used as a representation of the environment. However, to the best of our knowledge, the integration of EDFs into heuristic planning has been carried out in a loosely coupled fashion, dismissing EDF properties that can be used to accelerate/improve the planning process and enhance the safety margins of the resultant trajectories. This paper presents a fa…

Tru-POMDP: Task Planning Under Uncertainty via Tree of Hypotheses and Open-Ended POMDPs
Wenjing Tang, Xinyu He, Yongxi Huang, Yunxiao Xiao, Cewu Lu, Panpan Cai
https://arxiv.org/abs/2506.02860

Tru-POMDP: Task Planning Under Uncertainty via Tree of Hypotheses and Open-Ended POMDPs
Task planning under uncertainty is essential for home-service robots operating in the real world. Tasks involve ambiguous human instructions, hidden or unknown object locations, and open-vocabulary object types, leading to significant open-ended uncertainty and a boundlessly large planning space. To address these challenges, we propose Tru-POMDP, a planner that combines structured belief generation using Large Language Models (LLMs) with principled POMDP planning. Tru-POMDP introduces a hierarc…

The Trump regime's coordinated repression did not come from nowhere.
In 2024, TheNew York Times reported that the Trump transition team was already planning to use emergency powers, such as the one Trump invoked on June 7,
to confront political opponents who protest the administration.
While the Trump administration planned this move for about a year,
the deployment of troops in Los Angeles is the brutal culmination of a yearslong campaign to systematically erod…

Military Crackdown on LA Protests Portends Further Erosion of Everyone’s Rights
Governments at all levels from both parties have paved the way to an authoritarian response to dissent.

Deep Reinforcement Learning-Based Motion Planning and PDE Control for Flexible Manipulators
Amir Hossein Barjini, Seyed Adel Alizadeh Kolagar, Sadeq Yaqubi, Jouni Mattila
https://arxiv.org/abs/2506.08639

Deep Reinforcement Learning-Based Motion Planning and PDE Control for Flexible Manipulators
This article presents a motion planning and control framework for flexible robotic manipulators, integrating deep reinforcement learning (DRL) with a nonlinear partial differential equation (PDE) controller. Unlike conventional approaches that focus solely on control, we demonstrate that the desired trajectory significantly influences endpoint vibrations. To address this, a DRL motion planner, trained using the soft actor-critic (SAC) algorithm, generates optimized trajectories that inherently …

Dynamic real-time multi-UAV cooperative mission planning method under multiple constraints
Chenglou Liu, Yufeng Lu, Fangfang Xie, Tingwei Ji, Yao Zheng
https://arxiv.org/abs/2506.02365

Dynamic real-time multi-UAV cooperative mission planning method under multiple constraints
As UAV popularity soars, so does the mission planning associated with it. The classical approaches suffer from the triple problems of decoupled of task assignment and path planning, poor real-time performance and limited adaptability. Aiming at these challenges, this paper proposes a dynamic real-time multi-UAV collaborative mission planning algorithm based on Dubins paths under a distributed formation structure. Dubins path with multiple advantages bridges the gap between task assignment and p…

Attention-based Learning for 3D Informative Path Planning
Rui Zhao, Xingjian Zhang, Yuhong Cao, Yizhuo Wang, Guillaume Sartoretti
https://arxiv.org/abs/2506.08434

Attention-based Learning for 3D Informative Path Planning
In this work, we propose an attention-based deep reinforcement learning approach to address the adaptive informative path planning (IPP) problem in 3D space, where an aerial robot equipped with a downward-facing sensor must dynamically adjust its 3D position to balance sensing footprint and accuracy, and finally obtain a high-quality belief of an underlying field of interest over a given domain (e.g., presence of specific plants, hazardous gas, geological structures, etc.). In adaptive IPP task…

End-to-End Framework for Robot Lawnmower Coverage Path Planning using Cellular Decomposition
Nikunj Shah, Utsav Dey, Kenji Nishimiya
https://arxiv.org/abs/2506.06028

End-to-End Framework for Robot Lawnmower Coverage Path Planning using Cellular Decomposition
Efficient Coverage Path Planning (CPP) is necessary for autonomous robotic lawnmowers to effectively navigate and maintain lawns with diverse and irregular shapes. This paper introduces a comprehensive end-to-end pipeline for CPP, designed to convert user-defined boundaries on an aerial map into optimized coverage paths seamlessly. The pipeline includes user input extraction, coordinate transformation, area decomposition and path generation using our novel AdaptiveDecompositionCPP algorithm, pr…

Leveraging LLMs for Mission Planning in Precision Agriculture
Marcos Abel Zuzu\'arregui, Stefano Carpin
https://arxiv.org/abs/2506.10093 https://

Leveraging LLMs for Mission Planning in Precision Agriculture
Robotics and artificial intelligence hold significant potential for advancing precision agriculture. While robotic systems have been successfully deployed for various tasks, adapting them to perform diverse missions remains challenging, particularly because end users often lack technical expertise. In this paper, we present an end-to-end system that leverages large language models (LLMs), specifically ChatGPT, to enable users to assign complex data collection tasks to autonomous robots using na…

A Hybrid Approach to Indoor Social Navigation: Integrating Reactive Local Planning and Proactive Global Planning
Arnab Debnath, Gregory J. Stein, Jana Kosecka
https://arxiv.org/abs/2506.02593

A Hybrid Approach to Indoor Social Navigation: Integrating Reactive Local Planning and Proactive Global Planning
We consider the problem of indoor building-scale social navigation, where the robot must reach a point goal as quickly as possible without colliding with humans who are freely moving around. Factors such as varying crowd densities, unpredictable human behavior, and the constraints of indoor spaces add significant complexity to the navigation task, necessitating a more advanced approach. We propose a modular navigation framework that leverages the strengths of both classical methods and deep rei…

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture
Marcos Abel Zuzu\'arregui, Mustafa Melih Toslak, Stefano Carpin
https://arxiv.org/abs/2506.10106

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture
Artificial intelligence is transforming precision agriculture, offering farmers new tools to streamline their daily operations. While these technological advances promise increased efficiency, they often introduce additional complexity and steep learning curves that are particularly challenging for non-technical users who must balance tech adoption with existing workloads. In this paper, we present a natural language (NL) robotic mission planner that enables non-specialists to control heterogen…

Enhanced Trust Region Sequential Convex Optimization for Multi-Drone Thermal Screening Trajectory Planning in Urban Environments
Kaiyuan Chen, Zhengjie Hu, Shaolin Zhang, Yuanqing Xia, Wannian Liang, Shuo Wang
https://arxiv.org/abs/2506.06012

Enhanced Trust Region Sequential Convex Optimization for Multi-Drone Thermal Screening Trajectory Planning in Urban Environments
The rapid detection of abnormal body temperatures in urban populations is essential for managing public health risks, especially during outbreaks of infectious diseases. Multi-drone thermal screening systems offer promising solutions for fast, large-scale, and non-intrusive human temperature monitoring. However, trajectory planning for multiple drones in complex urban environments poses significant challenges, including collision avoidance, coverage efficiency, and constrained flight environmen…

TACS-Graphs: Traversability-Aware Consistent Scene Graphs for Ground Robot Indoor Localization and Mapping
Jeewon Kim, Minho Oh, Hyun Myung
https://arxiv.org/abs/2506.14178

TACS-Graphs: Traversability-Aware Consistent Scene Graphs for Ground Robot Indoor Localization and Mapping
Scene graphs have emerged as a powerful tool for robots, providing a structured representation of spatial and semantic relationships for advanced task planning. Despite their potential, conventional 3D indoor scene graphs face critical limitations, particularly under- and over-segmentation of room layers in structurally complex environments. Under-segmentation misclassifies non-traversable areas as part of a room, often in open spaces, while over-segmentation fragments a single room into overla…

ros2 fanuc interface: Design and Evaluation of a Fanuc CRX Hardware Interface in ROS2
Paolo Franceschi, Marco Faroni, Stefano Baraldo, Anna Valente
https://arxiv.org/abs/2506.14487

ros2 fanuc interface: Design and Evaluation of a Fanuc CRX Hardware Interface in ROS2
This paper introduces the ROS2 control and the Hardware Interface (HW) integration for the Fanuc CRX- robot family. It explains basic implementation details and communication protocols, and its integration with the Moveit2 motion planning library. We conducted a series of experiments to evaluate relevant performances in the robotics field. We tested the developed ros2_fanuc_interface for four relevant robotics cases: step response, trajectory tracking, collision avoidance integrated with Moveit…

A Point Cloud Completion Approach for the Grasping of Partially Occluded Objects and Its Applications in Robotic Strawberry Harvesting
Ali Abouzeid, Malak Mansour, Chengsong Hu, Dezhen Song
https://arxiv.org/abs/2506.14066

A Point Cloud Completion Approach for the Grasping of Partially Occluded Objects and Its Applications in Robotic Strawberry Harvesting
In robotic fruit picking applications, managing object occlusion in unstructured settings poses a substantial challenge for designing grasping algorithms. Using strawberry harvesting as a case study, we present an end-to-end framework for effective object detection, segmentation, and grasp planning to tackle this issue caused by partially occluded objects. Our strategy begins with point cloud denoising and segmentation to accurately locate fruits. To compensate for incomplete scans due to occlu…

Quadrotor Morpho-Transition: Learning vs Model-Based Control Strategies
Ioannis Mandralis, Richard M. Murray, Morteza Gharib
https://arxiv.org/abs/2506.14039

Quadrotor Morpho-Transition: Learning vs Model-Based Control Strategies
Quadrotor Morpho-Transition, or the act of transitioning from air to ground through mid-air transformation, involves complex aerodynamic interactions and a need to operate near actuator saturation, complicating controller design. In recent work, morpho-transition has been studied from a model-based control perspective, but these approaches remain limited due to unmodeled dynamics and the requirement for planning through contacts. Here, we train an end-to-end Reinforcement Learning (RL) controll…

Attention-Based Map Encoding for Learning Generalized Legged Locomotion
Junzhe He, Chong Zhang, Fabian Jenelten, Ruben Grandia, Moritz B\"Acher, Marco Hutter
https://arxiv.org/abs/2506.09588

Attention-Based Map Encoding for Learning Generalized Legged Locomotion
Dynamic locomotion of legged robots is a critical yet challenging topic in expanding the operational range of mobile robots. It requires precise planning when possible footholds are sparse, robustness against uncertainties and disturbances, and generalizability across diverse terrains. While traditional model-based controllers excel at planning on complex terrains, they struggle with real-world uncertainties. Learning-based controllers offer robustness to such uncertainties but often lack preci…

An Improved Grey Wolf Optimizer Inspired by Advanced Cooperative Predation for UAV Shortest Path Planning
Zuhao Teng, Qian Dong, Ze Zhang, Shuangyao Huang, Wenzhang Zhang, Jingchen Wang, Ji Li, Xi Chen
https://arxiv.org/abs/2506.03663

An Improved Grey Wolf Optimizer Inspired by Advanced Cooperative Predation for UAV Shortest Path Planning
With the widespread application of Unmanned Aerial Vehicles (UAVs) in domains like military reconnaissance, emergency rescue, and logistics delivery, efficiently planning the shortest flight path has become a critical challenge. Traditional heuristic-based methods often suffer from the inability to escape from local optima, which limits their effectiveness in finding the shortest path. To address these issues, a novel Improved Grey Wolf Optimizer (IGWO) is presented in this study. The proposed …

Sparse Imagination for Efficient Visual World Model Planning
Junha Chun, Youngjoon Jeong, Taesup Kim
https://arxiv.org/abs/2506.01392 https://

Sparse Imagination for Efficient Visual World Model Planning
World model based planning has significantly improved decision-making in complex environments by enabling agents to simulate future states and make informed choices. However, ensuring the prediction accuracy of world models often demands substantial computational resources, posing a major challenge for real-time applications. This computational burden is particularly restrictive in robotics, where resources are severely constrained. To address this limitation, we propose a Sparse Imagination fo…

This https://arxiv.org/abs/2502.20636 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Delayed-Decision Motion Planning in the Presence of Multiple Predictions
Reliable automated driving technology is challenged by various sources of uncertainties, in particular, behavioral uncertainties of traffic agents. It is common for traffic agents to have intentions that are unknown to others, leaving an automated driving car to reason over multiple possible behaviors. This paper formalizes a behavior planning scheme in the presence of multiple possible futures with corresponding probabilities. We present a maximum entropy formulation and show how, under certai…

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[1/2]:
Bridging the Gap between Discrete Agent Strategies in Game Theory and Continuous Motion Planning ...

This https://arxiv.org/abs/2410.03483 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Versatile Neural Network Configuration Space Planning and Control Strategy for Modular Soft Robot Arms
Modular soft robot arms (MSRAs) are composed of multiple modules connected in a sequence, and they can bend at different angles in various directions. This capability allows MSRAs to perform more intricate tasks than single-module robots. However, the modular structure also induces challenges in accurate planning and control. Nonlinearity and hysteresis complicate the physical model, while the modular structure and increased DOFs further lead to cumulative errors along the sequence. To address …

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Hongjun Wu, Heng Zhang, Pengsong Zhang, Jin Wang, Cong Wang
https://arxiv.org/abs/2506.08296

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Recent advances in multimodal vision-language-action (VLA) models have revolutionized traditional robot learning, enabling systems to interpret vision, language, and action in unified frameworks for complex task planning. However, mastering complex manipulation tasks remains an open challenge, constrained by limitations in persistent contextual memory, multi-agent coordination under uncertainty, and dynamic long-horizon planning across variable sequences. To address this challenge, we propose \…