1 research outputs found
Control Barrier Functions in UGVs for Kinematic Obstacle Avoidance: A Collision Cone Approach
In this paper, we propose a new class of Control Barrier Functions (CBFs) for
Unmanned Ground Vehicles (UGVs) that help avoid collisions with kinematic
(non-zero velocity) obstacles. While the current forms of CBFs have been
successful in guaranteeing safety/collision avoidance with static obstacles,
extensions for the dynamic case with torque/acceleration-controlled unicycle
and bicycle models have seen limited success. Moreover, with these nonholonomic
UGV models, applications of existing CBFs have been conservative in terms of
control, i.e., steering/thrust control has not been possible under certain
common scenarios. Drawing inspiration from the classical use of collision cones
for obstacle avoidance in path planning, we introduce its novel CBF formulation
with theoretical guarantees on safety for both the unicycle and bicycle models.
The main idea is to ensure that the velocity of the obstacle w.r.t. the vehicle
is always pointing away from the vehicle. Accordingly, we construct a
constraint that ensures that the velocity vector always avoids a cone of
vectors pointing at the vehicle. The efficacy of this new control methodology
is experimentally verified on the Copernicus mobile robot. We further extend it
to the bicycle model and demonstrate collision avoidance under various
scenarios in the CARLA simulator.Comment: Submitted to 2023 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS). 8 pages, 8 figures, For supplement video follow
https://youtu.be/4qWYaWEPduM. The first and second authors have contributed
equall