2025
Sensorimotor Learning With Stability Guarantees via Autonomous Neural Dynamic Policies
Dionis Totsila, Konstantinos I. Chatzilygeroudis, Valerio Modugno, Denis Hadjivelichkov, Dimitrios Kanoulas
RA-L 2025
State-of-the-art sensorimotor learning algorithms, either in the context of reinforcement learning or imitation learning, offer policies that can often produce unstable behaviors, damaging the robot and/or the environment. Moreover, it is very difficult to interpret the optimized controller and anal