Paper Info
Title
Fast Generation of Collision-Free Trajectories for Robot Swarms Using GPU Acceleration.
Abstract
As the capabilities of robots and their control systems improve, we see an increasing number of use cases where the simultaneous operation of robots within a space is advantageous. Although trajectories for individual robots can be computed quickly using the existing methods, when robots operate simultaneously and in close proximity, the requirement for collision avoidance introduces a coupling between robot trajectories and makes the trajectory generation problem difficult to solve quickly. In this paper, we propose a parallelizable formulation of such problems and a method for solving them quickly on modern graphics processing units, using momentum-based gradient descent. We demonstrate the proposed framework in simulation using two case studies: a swarm of 200 quadcopters traversing a maze and a fleet of 100 bicycle robots changing their formation. In both the cases, our method requires just seconds to generate feasible, collision-free trajectories for the entire swarm.
Year
DOI
Venue
2019
10.1109/ACCESS.2018.2889533
IEEE ACCESS
Keywords
Field
DocType
Collision avoidance,motion planning,robot control,trajectory optimization
Graphics,Gradient descent,Swarm behaviour,Computer science,Real-time computing,Collision,Acceleration,Control system,Robot,Trajectory,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
1
PageRank 
References 
Authors
0.37
0
3
Name
Order
Citations
PageRank
Michael Hamer131.44
Lino Widmer210.37
Raffaello D'andrea31592162.96