dPMP-Deep Probabilistic Motion Planning: A use case in Strawberry Picking Robot
Alessandra Tafuro,Bappaditya Debnath,Andrea M. Zanchettin,E. Amir Ghalamzan,Alessandra Tafuro,Bappaditya Debnath,Andrea M. Zanchettin,E. Amir Ghalamzan
This paper presents a novel probabilistic approach to deep robot learning from demonstrations (LfD). Deep move-ment primitives (DMPs) are deterministic LfD model that maps visual information directly into a robot trajectory. This paper extends DMPs and presents a deep probabilistic model that maps the visual information into a distribution of effective robot trajectories. The architecture that lea...