3 papers
cs.RO2026
Direct Rotor Thrust Sensing and Feedback Control for Disturbance Rejection of Multirotors Using Load-cells
Peter Böhm, Michael Brünig, Peyman Z. Moghadam +1
Gust disturbances, dynamic vertical inflow and ground effect are key adverse aerodynamic phenomena that induce variations in the forces acting on a multirotor and complicate its fl…
cs.LG2025
Low-cost Real-world Implementation of the Swing-up Pendulum for Deep Reinforcement Learning Experiments
Peter Böhm, Pauline Pounds, Archie C. Chapman
Deep reinforcement learning (DRL) has had success in virtual and simulated domains, but due to key differences between simulated and real-world environments, DRL-trained policies h…
cs.RO2025
Training Directional Locomotion for Quadrupedal Low-Cost Robotic Systems via Deep Reinforcement Learning
Peter Böhm, Archie C. Chapman, Pauline Pounds
In this work we present Deep Reinforcement Learning (DRL) training of directional locomotion for low-cost quadrupedal robots in the real world. In particular, we exploit randomizat…