Safe Planning for Articulated Robots Using Reachability-based Obstacle Avoidance With Spheres
CoRR(2024)
摘要
Generating safe motion plans in real-time is necessary for the wide-scale
deployment of robots in unstructured and human-centric environments. These
motion plans must be safe to ensure humans are not harmed and nearby objects
are not damaged. However, they must also be generated in real-time to ensure
the robot can quickly adapt to changes in the environment. Many trajectory
optimization methods introduce heuristics that trade-off safety and real-time
performance, which can lead to potentially unsafe plans. This paper addresses
this challenge by proposing Safe Planning for Articulated Robots Using
Reachability-based Obstacle Avoidance With Spheres (SPARROWS). SPARROWS is a
receding-horizon trajectory planner that utilizes the combination of a novel
reachable set representation and an exact signed distance function to generate
provably-safe motion plans. At runtime, SPARROWS uses parameterized
trajectories to compute reachable sets composed entirely of spheres that
overapproximate the swept volume of the robot's motion. SPARROWS then performs
trajectory optimization to select a safe trajectory that is guaranteed to be
collision-free. We demonstrate that SPARROWS' novel reachable set is
significantly less conservative than previous approaches. We also demonstrate
that SPARROWS outperforms a variety of state-of-the-art methods in solving
challenging motion planning tasks in cluttered environments. Code, data, and
video demonstrations can be found at
.
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