1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.RO2024
Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning
Piotr Kicki, Davide Tateo, Puze Liu +3
Trajectory planning under kinodynamic constraints is fundamental for advanced robotics applications that require dexterous, reactive, and rapid skills in complex environments. Thes…
cs.RO2023★ 1 cited
Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks
Piotr Kicki, Puze Liu, Davide Tateo +4
Motion planning is a mature area of research in robotics with many well-established methods based on optimization or sampling the state space, suitable for solving kinematic motion…