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We present an approach to learn fast and dynamic robot motions without exceeding limits on the position $\theta$, velocity $\dot{\theta}$, acceleration $\ddot{\theta}$ and jerk $\dddot{\theta}$ of each robot joint. Movements are generated…

Robotics · Computer Science 2021-03-30 Jonas C. Kiemel , Torsten Kröger

This paper studies motion planning of a mobile robot under uncertainty. The control objective is to synthesize a {finite-memory} control policy, such that a high-level task specified as a Linear Temporal Logic (LTL) formula is satisfied…

Robotics · Computer Science 2017-10-24 Meng Guo , Michael M. Zavlanos

Decisions in automated logistic systems can be improved based on knowledge of real-time state of individual parts and also environmental factors. These knowledge can be obtained through travel time of edges by individual robots which…

Systems and Control · Computer Science 2018-05-16 Pragna Das , Lluis Ribas-Xirgo

Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic tasks, the presence of unmodeled dynamics renders the motion…

Robotics · Computer Science 2019-02-11 Ruben Grandia , Farbod Farshidian , Alexey Dosovitskiy , René Ranftl , Marco Hutter

This paper addresses the problem of coordination of a fleet of mobile robots - the problem of finding an optimal set of collision-free trajectories for individual robots in the fleet. Many approaches have been introduced during the last…

Robotics · Computer Science 2019-01-23 Jakub Hvězda , Miroslav Kulich , Libor Přeučil

Robotic systems often operate with uncertainties in their dynamics, for example, unknown inertial properties. Broadly, there are two approaches for controlling uncertain systems: design robust controllers in spite of uncertainty, or…

Robotics · Computer Science 2019-06-10 Keenan Albee , Monica Ekal , Rodrigo Ventura , Richard Linares

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

Inspired by sled-pulling dogs in transportation, we present a cable-trailer integrated with a quadruped robot system. The motion planning of this system faces challenges due to the interactions between the cable's state transitions, the…

Robotics · Computer Science 2025-12-23 Wentao Zhang , Shaohang Xu , Gewei Zuo , Bolin Li , Jingbo Wang , Lijun Zhu

Coordinated operations of multi-robot systems (MRS) require agents to maintain communication connections to accomplish team objectives. However, maintaining the connections imposes costs in terms of restricted robot mobility, resulting in…

Optimization and Control · Mathematics 2026-03-17 Kunal Garg , Xi Yu

Multi-robot coordination is crucial for autonomous systems, yet real-world deployments often encounter various failures. These include both temporary and permanent disruptions in sensing and communication, which can significantly degrade…

Robotics · Computer Science 2025-08-11 Peihan Li , Jiazhen Liu , Yuwei Wu , Lifeng Zhou

Quadrotors are among the most agile flying robots. However, planning time-optimal trajectories at the actuation limit through multiple waypoints remains an open problem. This is crucial for applications such as inspection, delivery, search…

Robotics · Computer Science 2021-10-04 Philipp Foehn , Angel Romero , Davide Scaramuzza

Multi-agent reinforcement learning systems deployed in real-world robotics applications face severe communication constraints that significantly impact coordination effectiveness. We present a framework that combines information bottleneck…

Robotics · Computer Science 2026-02-03 Ahmad Farooq , Kamran Iqbal

Bearing measurements,as the most common modality in nature, have recently gained traction in multi-robot systems to enhance mutual localization and swarm collaboration. Despite their advantages, challenges such as sensory noise, obstacle…

Robotics · Computer Science 2024-01-17 Yingjian Wang , Xiangyong Wen , Fei Gao

This paper addresses security challenges in multi-robot systems (MRS) where adversaries may compromise robot control, risking unauthorized access to forbidden areas. We propose a novel multi-robot optimal planning algorithm that integrates…

Robotics · Computer Science 2025-09-03 Ziqi Yang , Roberto Tron

This paper considers the problem of assigning multiple mobile robots to goals on transport networks with uncertain information about travel times. Our aim is to produce optimal assignments, such that the average waiting time at destinations…

Robotics · Computer Science 2019-04-23 Amanda Prorok

The fundamental goal assignment problem for a multi-robot application aims to assign a unique goal to each robot while ensuring collision-free paths, minimizing the total movement cost. A plausible algorithmic solution to this NP-hard…

Multiagent Systems · Computer Science 2024-02-22 Aakash , Indranil Saha

Trajectory planning for mobile robots in cluttered environments remains a major challenge due to narrow passages, where conventional methods often fail or generate suboptimal paths. To address this issue, we propose the adaptive trajectory…

Robotics · Computer Science 2025-10-31 Hahjin Lee , Young J. Kim

A new path planning method for Mobile Robots (MR) has been developed and implemented. On the one hand, based on the shortest path from the start point to the goal point, this path planner can choose the best moving directions of the MR,…

Robotics · Computer Science 2016-09-08 Hoc Thai Nguyen , Hai Xuan Le

Communication bandwidth is an important consideration in multi-robot exploration, where information exchange among robots is critical. While existing methods typically aim to reduce communication throughput, they either require significant…

Robotics · Computer Science 2024-07-30 Yixiao Ma , Jingsong Liang , Yuhong Cao , Derek Ming Siang Tan , Guillaume Sartoretti

This paper develops a path planner that minimizes risk (e.g. motion execution) while maximizing accumulated reward (e.g., quality of sensor viewpoint) motivated by visual assistance or tracking scenarios in unstructured or confined…

Robotics · Computer Science 2019-03-11 Xuesu Xiao , Jan Dufek , Robin Murphy
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