SIPP: Safe interval path planning for dynamic environments

By Mike Phillips, Maxim Likhachev. IEEE International Conference on Robotics and Automation, 2011

381 citations recorded by the source corpus.

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Scene Understanding by Reasoning Stability and Safety (2015, background): “(4) Safe motion planning As motion planning is a classic problem in robotics, (Petti and Fraichard 2005; Phillips and Likhachev 2011) tackled the problem of safe motion planning in the presence of moving obstacles.”
Detecting potential falling objects by inferring human action and natural disturbance (2014, background): “As the planning is a classic problem in robotics, Petti and Fraichard [22], Phillips and Likhachev [23] tackled the problem of safe motion planning in the presence of moving obstacles.”
Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning (2016, background): “A subclass of noncooperative approaches [14], [15] propagates the other agents’ dynamics forward in time, and then plans a collision-free path with respect to the other agents’ predicted paths.”
Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks (2019, background): “Yakovlev and Andreychuk (2017) proposed a hybrid of the SIPP algorithm (Phillips and Likhachev 2011) and prioritized planning for weighted graphs.”
Mobile Robot Path Planning in Dynamic Environments Through Globally Guided Reinforcement Learning (2020, positive): “If the future movements of obstacles are unknown, one may attempt to model the behavior of dynamic obstacles and predict their paths [5].”
Human-aware robot navigation: A survey (2013, neutral): “Likhachev in [75].”