Continuous-time Gaussian Process Trajectory Generation for Multi-robot Formation via Probabilistic Inference
Shuang Guo,Bo Liu,Shen Zhang,Jifeng Guo,Changhong Wang,Shuang Guo,Bo Liu,Shen Zhang,Jifeng Guo,Changhong Wang
In this paper, we extend a famous motion planning approach, GPMP2, to multi-robot cases, yielding a novel centralized trajectory generation method for the multi-robot formation. A sparse Gaussian Process model is employed to represent the continuous-time trajectories of all robots as a limited number of states, which improves computational efficiency due to the sparsity. We add constraints to guar...
