Anticipate your surroundings: Predictive collision detection between dynamic obstacles and planned robot trajectories on the GPU

Abstract

Proactive collision detection enables robots to efficiently execute tasks in shared human-robot-workspaces by avoiding collision-prone situations. Our work connects motion prediction of RGB-D flow algorithms with motion primitive planning via an efficient voxel Swept-Volume-based collision detection. The approach can handle scenarios with varying contents as we use the same techniques to predict single moving objects but also articulated bodies. Our process chain consists of highly parallel GPU algorithms that allow a full 3D representation of planned trajectories and predictions from live pointclouds in high resolution, while still being online capable. We demonstrated our achievements in two scenarios with different motion granularity.