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Related papers: RLSS: Real-time Multi-Robot Trajectory Replanning …

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In this letter, an integrated task planning and reactive motion planning framework termed Multi-FLEX is presented that targets real-world, industrial multi-robot applications. Reactive motion planning has been attractive for the purposes of…

This work deals with the problem of planning conflict-free paths for mobile robots in cluttered environments. Since centralized, coupled planning algorithms are computationally intractable for large numbers of robots, we consider decoupled…

Robotics · Computer Science 2019-08-08 Wenying Wu , Subhrajit Bhattacharya , Amanda Prorok

This paper presents a collection of path planning algorithms for real-time movement of multiple robots across a Robotic Mobile Fulfillment System (RMFS). Robots are assigned to move storage units to pickers at working stations instead of…

Artificial Intelligence · Computer Science 2018-11-20 Marius Merschformann , Lin Xie , Daniel Erdmann

Robot swarms navigating through unknown obstacle environments are an emerging research area that faces challenges. Performing tasks in such environments requires swarms to achieve autonomous localization, perception, decision-making,…

Robotics · Computer Science 2026-04-27 Pengda Mao , Shuli Lv , Chen Min , Zhaolong Shen , Quan Quan

In applications such as search and rescue or disaster relief, heterogeneous multi-robot systems (MRS) can provide significant advantages for complex objectives that require a suite of capabilities. However, within these application spaces,…

Robotics · Computer Science 2023-08-04 Lauren Bramblett , Nicola Bezzo

Planning collision-free paths for multi-robot systems (MRS) is a challenging problem because of the safety and efficiency constraints required for real-world solutions. Even though coupled path planning approaches provide optimal…

Robotics · Computer Science 2021-01-07 Aditya Rathi , Rohith G , Madhu Vadali

One of the pivotal challenges in a multi-robot system is how to give attention to accuracy and efficiency while ensuring safety. Prior arts cannot strictly guarantee collision-free for an arbitrarily large number of robots or the results…

Robotics · Computer Science 2025-01-08 Xiaoxiao Li , Zhirui Sun , Mansha Zheng , Hongpeng Wang , Shuai Li , Jiankun Wang

We present progress on the problem of reconfiguring a 2D arrangement of building material by a cooperative group of robots. These robots must avoid collisions, deadlocks, and are subjected to the constraint of maintaining connectivity of…

It is crucial to efficiently execute instructions such as "Find an apple and a banana" or "Get ready for a field trip," which require searching for multiple objects or understanding context-dependent commands. This study addresses the…

Multiple mobile robots play a significant role in various spatially distributed tasks.In unfamiliar and non-repetitive scenarios, reconstructing the global map is time-inefficient and sometimes unrealistic. Hence, research has focused on…

Robotics · Computer Science 2025-12-29 Weining Lu , Qingquan Lin , Litong Meng , Chenxi Li , Bin Liang

On-line motion planning in unknown environments is a challenging problem as it requires (i) ensuring collision avoidance and (ii) minimizing the motion time, while continuously predicting where to go next. Previous approaches to on-line…

Robotics · Computer Science 2017-09-05 Sanjeev Sharma

Multi-robot path finding in dynamic environments is a highly challenging classic problem. In the movement process, robots need to avoid collisions with other moving robots while minimizing their travel distance. Previous methods for this…

Artificial Intelligence · Computer Science 2025-12-12 Shaoming Peng

Safety remains a central obstacle preventing widespread use of RL in the real world: learning new tasks in uncertain environments requires extensive exploration, but safety requires limiting exploration. We propose Recovery RL, an algorithm…

Robot navigation in dense human crowds poses a significant challenge due to the complexity of human behavior in dynamic and obstacle-rich environments. In this work, we propose a dynamic weight adjustment scheme using a neural network to…

Robotics · Computer Science 2024-12-03 Muqing Cao , Xinhang Xu , Yizhuo Yang , Jianping Li , Tongxing Jin , Pengfei Wang , Tzu-Yi Hung , Guosheng Lin , Lihua Xie

Industrial robots are widely used in diverse manufacturing environments. Nonetheless, how to enable robots to automatically plan trajectories for changing tasks presents a considerable challenge. Further complexities arise when robots…

Robotics · Computer Science 2025-02-27 Siddharth Singh , Tian Yu , Qing Chang , John Karigiannis , Shaopeng Liu

Generating time-optimal, collision-free trajectories for autonomous mobile robots involves a fundamental trade-off between guaranteeing safety and managing computational complexity. State-of-the-art approaches formulate spline-based motion…

Robotics · Computer Science 2026-03-26 Dries Dirckx , Jan Swevers , Wilm Decré

We investigate the problem of multi-robot coordinated planning in environments where the robots may have to operate in close proximity to each other. We seek computationally efficient planners that ensure safe paths and adherence to…

Multiagent Systems · Computer Science 2019-10-09 Clayton Mangette , Pratap Tokekar

Autonomous exploration in unknown environments remains a fundamental challenge in robotics, particularly for applications such as search and rescue, industrial inspection, and planetary exploration. Multi-robot active SLAM presents a…

Stable dynamical systems are a flexible tool to plan robotic motions in real-time. In the robotic literature, dynamical system motions are typically planned without considering possible limitations in the robot's workspace. This work…

Robotics · Computer Science 2020-03-26 Matteo Saveriano , Dongheui Lee

Trajectory optimization methods have achieved an exceptional level of performance on real-world robots in recent years. These methods heavily rely on accurate analytical models of the dynamics, yet some aspects of the physical world can…