Path Planning with Kinematic Constraints for Robot Groups
This addresses the problem of applying abstract path planning solutions to actual robots by considering real-world constraints, though it is incremental as it builds on existing solvers.
The paper tackled path planning for multiple robots by incorporating kinematic constraints like maximum velocities and ensuring a minimum safety distance, demonstrating the approach in simulation and on real robots in 2D and 3D environments.
Path planning for multiple robots is well studied in the AI and robotics communities. For a given discretized environment, robots need to find collision-free paths to a set of specified goal locations. Robots can be fully anonymous, non-anonymous, or organized in groups. Although powerful solvers for this abstract problem exist, they make simplifying assumptions by ignoring kinematic constraints, making it difficult to use the resulting plans on actual robots. In this paper, we present a solution which takes kinematic constraints, such as maximum velocities, into account, while guaranteeing a user-specified minimum safety distance between robots. We demonstrate our approach in simulation and on real robots in 2D and 3D environments.