Learning from demonstration (LfD) represents an effective method for generating a trajectory with prior knowledge obtained from demonstrations. The adaption and generalization abilities are crucial to the application of the LfD method. We present a novel trajectory generation method based on spatio-temporal templates. A trajectory is generated by evaluating the similarity between a spatio-temporal template and features of the generated trajectory. In this way, the spatio-temporal features of the trajectory are maintained based on the prerequisites from task specifications and environmental constraints. The effectiveness of our method is verified through synthetic trajectories and using the Pioneer-3AT wheeled mobile robot platform.
['Xiaochuan Yin', 'Qijun Chen']
Trajectory Generation With Spatio-Temporal Templates Learned From Demonstrations