Prioritized motion planning for multiple robots

By Jur van den Berg, Mark H. Overmars. 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005

323 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/c5a1cd69a30e7384405851689eacd6db7d348fa2

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Optimal Multirobot Path Planning on Graphs: Complete Algorithms and Effective Heuristics (2015, background): “…Kloder and Hutchinson (2006); Ryan (2008); Jansen and Sturtevant (2008); Surynek (2009); Luna and Bekris (2011); Standley and Korf (2011); van den Berg and Overmars (2005); van den Berg et al. (2009); Solovey and Halperin (2012); Yu and LaValle (2013a); Turpin et al. (2014); Solovey et al.…”
Subdimensional expansion for multirobot path planning (2015, background): “The choice of priority ordering is critical, leading to a number of heuristics for choosing priority orders that are likely to lead to a solution [38, 40, 41].”
Graph Neural Networks for Decentralized Multi-Robot Path Planning (2019, methodology): “For each panel, we train a model for N ∈ [4, 6, 8, 10, 12], and test it on instances of the same robot team size.”
Searching with Consistent Prioritization for Multi-Agent Path Finding (2018, background): “We consider the following algorithms: CBS-H (labeled CBS) is a state-of-theart implementation of CBS (Felner et al. 2018); FIX is a PBS variant with a total priority ordering specified by the order of the agents in the MAPF instances, which simulates CA* (Silver 2005); LH is a PBS variant with a fix”
Learning a Decentralized Multi-arm Motion Planner (2020, background): “While traditional centralized motion planner [1, 2, 3, 4, 5, 6] beneﬁt from having access to all the information a motion planner module might need, these approaches fail to scale efﬁciently with the number of arms in the system (the team size) because their centralized components can become the…”
Planning algorithms (2006, background): “A straightforward approach to decoupled planning is to sort the robots by priority and plan for higher priority robots first [322, 951].”