Zobrazeno 1 - 10
of 206
pro vyhledávání: '"Cao, Yuhong"'
Autor:
Tan, Derek Ming Siang, Ma, Yixiao, Liang, Jingsong, Chng, Yi Cheng, Cao, Yuhong, Sartoretti, Guillaume
Information sharing is critical in time-sensitive and realistic multi-robot exploration, especially for smaller robotic teams in large-scale environments where connectivity may be sparse and intermittent. Existing methods often overlook such communic
Externí odkaz:
http://arxiv.org/abs/2409.04730
In this paper, we introduce HDPlanner, a deep reinforcement learning (DRL) based framework designed to tackle two core and challenging tasks for mobile robots: autonomous exploration and navigation, where the robot must optimize its trajectory adapti
Externí odkaz:
http://arxiv.org/abs/2408.03768
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 computatio
Externí odkaz:
http://arxiv.org/abs/2407.20203
In recent years, the field of aerial robotics has witnessed significant progress, finding applications in diverse domains, including post-disaster search and rescue operations. Despite these strides, the prohibitive acquisition costs associated with
Externí odkaz:
http://arxiv.org/abs/2406.16671
In this work, we propose a deep reinforcement learning (DRL) based reactive planner to solve large-scale Lidar-based autonomous robot exploration problems in 2D action space. Our DRL-based planner allows the agent to reactively plan its exploration p
Externí odkaz:
http://arxiv.org/abs/2403.10833
This work focuses on the persistent monitoring problem, where a set of targets moving based on an unknown model must be monitored by an autonomous mobile robot with a limited sensing range. To keep each target's position estimate as accurate as possi
Externí odkaz:
http://arxiv.org/abs/2303.06350
In multi-agent informative path planning (MAIPP), agents must collectively construct a global belief map of an underlying distribution of interest (e.g., gas concentration, light intensity, or pollution levels) over a given domain, based on measureme
Externí odkaz:
http://arxiv.org/abs/2303.05351
In autonomous robot exploration tasks, a mobile robot needs to actively explore and map an unknown environment as fast as possible. Since the environment is being revealed during exploration, the robot needs to frequently re-plan its path online, as
Externí odkaz:
http://arxiv.org/abs/2301.11575
Purpose of review: Recent advances in sensing, actuation, and computation have opened the door to multi-robot systems consisting of hundreds/thousands of robots, with promising applications to automated manufacturing, disaster relief, harvesting, las
Externí odkaz:
http://arxiv.org/abs/2204.03516
DAN: Decentralized Attention-based Neural Network for the MinMax Multiple Traveling Salesman Problem
The multiple traveling salesman problem (mTSP) is a well-known NP-hard problem with numerous real-world applications. In particular, this work addresses MinMax mTSP, where the objective is to minimize the max tour length among all agents. Many roboti
Externí odkaz:
http://arxiv.org/abs/2109.04205