Tootfinder

Risk Map As Middleware: Towards Interpretable Cooperative End-to-end Autonomous Driving for Risk-Aware Planning
Mingyue Lei, Zewei Zhou, Hongchen Li, Jiaqi Ma, Jia Hu
https://arxiv.org/abs/2508.07686

Risk Map As Middleware: Towards Interpretable Cooperative End-to-end Autonomous Driving for Risk-Aware Planning
End-to-end paradigm has emerged as a promising approach to autonomous driving. However, existing single-agent end-to-end pipelines are often constrained by occlusion and limited perception range, resulting in hazardous driving. Furthermore, their black-box nature prevents the interpretability of the driving behavior, leading to an untrustworthiness system. To address these limitations, we introduce Risk Map as Middleware (RiskMM) and propose an interpretable cooperative end-to-end driving frame…

Sensing with Mobile Devices through Radio SLAM: Models, Methods, Opportunities, and Challenges
Yu Ge, Ossi Kaltiokallio, Elizaveta Rastorgueva-Foi, Musa Furkan Keskin, Hui Chen, Guillaume Jornod, Jukka Talvitie, Mikko Valkama, Frank Hofmann, Henk Wymeersch
https://arxiv.org/abs/2509.07775

Sensing with Mobile Devices through Radio SLAM: Models, Methods, Opportunities, and Challenges
The integration of sensing and communication (ISAC) is a cornerstone of 6G, enabling simultaneous environmental awareness and communication. This paper explores radio SLAM (simultaneous localization and mapping) as a key ISAC approach, using radio signals for mapping and localization. We analyze radio SLAM across different frequency bands, discussing trade-offs in coverage, resolution, and hardware requirements. We also highlight opportunities for integration with sensing, positioning, and coop…

Behaviorally Heterogeneous Multi-Agent Exploration Using Distributed Task Allocation
Nirabhra Mandal, Aamodh Suresh, Carlos Nieto-Granda, Sonia Mart\'inez
https://arxiv.org/abs/2509.08242

Behaviorally Heterogeneous Multi-Agent Exploration Using Distributed Task Allocation
We study a problem of multi-agent exploration with behaviorally heterogeneous robots. Each robot maps its surroundings using SLAM and identifies a set of areas of interest (AoIs) or frontiers that are the most informative to explore next. The robots assess the utility of going to a frontier using Behavioral Entropy (BE) and then determine which frontier to go to via a distributed task assignment scheme. We convert the task assignment problem into a non-cooperative game and use a distributed alg…

Replaced article(s) found for q-bio.TO. https://arxiv.org/list/q-bio.TO/new
[1/1]:
- Panoramic Voltage-Sensitive Optical Mapping of Contracting Hearts using Cooperative Multi-View Mo...
Shrey Chowdhary, Jan Lebert, Shai Dickman, Charles Gordon, Jan Christoph

Replaced article(s) found for physics.med-ph. https://arxiv.org/list/physics.med-ph/new
[1/1]:
- Panoramic Voltage-Sensitive Optical Mapping of Contracting Hearts using Cooperative Multi-View Mo...
Shrey Chowdhary, Jan Lebert, Shai Dickman, Charles Gordon, Jan Christoph

Resolving Tangling in Multi-Conformer Refinement via Iterative Projections
Avinash Mandaiya, Veit Elser
https://arxiv.org/abs/2509.05189 https://arxiv.org/…

Resolving Tangling in Multi-Conformer Refinement via Iterative Projections
The advent of advanced crystallographic techniques has shifted structural biology from static, single-conformer models toward probing protein dynamics. Extracting cooperative motions from temporally and spatially averaged electron density maps requires both high-resolution data and refinement algorithms capable of handling conformational heterogeneity. However, current refinement protocols often fail due to the tangling phenomenon, in which conformational states become improperly intertwined du…

RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation
Xiucheng Wang, Qiming Zhang, Nan Cheng
https://arxiv.org/abs/2509.01875

RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation
Accurate localization of non-cooperative signal sources in non-line-of-sight (NLoS) environments remains a critical challenge with a wide range of applications, including autonomous navigation, industrial automation, and emergency response. In such settings, traditional positioning techniques relying on line-of-sight (LoS) or cooperative signaling fail due to severe multipath propagation and unknown transmit power. This paper proposes a novel generative inference framework for NLoS localization…

SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception
Melih Yazgan, Qiyuan Wu, Iramm Hamdard, Shiqi Li, J. Marius Zoellner
https://arxiv.org/abs/2508.13007

SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception
Collaborative perception allows connected autonomous vehicles (CAVs) to overcome occlusion and limited sensor range by sharing intermediate features. Yet transmitting dense Bird's-Eye-View (BEV) feature maps can overwhelm the bandwidth available for inter-vehicle communication. We present SlimComm, a communication-efficient framework that integrates 4D radar Doppler with a query-driven sparse scheme. SlimComm builds a motion-centric dynamic map to distinguish moving from static objects and gene…

Evolutionary dynamics under coordinated reciprocity
Feipeng Zhang, Bingxin Lin, Lei Zhou, Long Wang
https://arxiv.org/abs/2509.03524 https://arxiv.org/pdf/…

Evolutionary dynamics under coordinated reciprocity
Using past behaviors to guide future actions is essential for fostering cooperation in repeated social dilemmas. Traditional memory-based strategies that focus on recent interactions have yielded valuable insights into the evolution of cooperative behavior. However, as memory length increases, the complexity of analysis grows exponentially, since these strategies need to map every possible action sequence of a given length to subsequent responses. Due to their inherent reliance on exhaustive ma…