5 papers
Learning Variable Impedance Control for Contact Sensitive Tasks
Miroslav Bogdanovic, Majid Khadiv, Ludovic Righetti
Reinforcement learning algorithms have shown great success in solving different problems ranging from playing video games to robotics. However, they struggle to solve delicate robo…
Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning
Mohammad Hasan Yeganegi, Majid Khadiv, S. Ali A. Moosavian +3
Trajectory optimization (TO) is one of the most powerful tools for generating feasible motions for humanoid robots. However, including uncertainties and stochasticity in the TO pro…
Trajectory Optimization for Robust Humanoid Locomotion with Sample-Efficient Learning
Majid Khadiv, Mohammad Hasan Yeganegi, S. Ali A. Moosavian +2
Trajectory optimization (TO) is one of the most powerful tools for generating feasible motions for humanoid robots. However, including uncertainties and stochasticity in the TO pro…
A Reactive and Efficient Walking Pattern Generator for Robust Bipedal Locomotion
Fatemeh Nazemi, Aghil Yousefi-koma, Farzad A. shirazi +1
Available possibilities to prevent a biped robot from falling down in the presence of severe disturbances are mainly Center of Pressure (CoP) modulation, step location and timing a…
Pattern Generation for Walking on Slippery Terrains
Majid Khadiv, S. Ali A. Moosavian, Alexander Herzog +1
In this paper, we extend state of the art Model Predictive Control (MPC) approaches to generate safe bipedal walking on slippery surfaces. In this setting, we formulate walking as…