193 citations · 386 across the 51 of their papers we have counts for
8 papers · 1 filter
Impedance Optimization for Uncertain Contact Interactions Through Risk Sensitive Optimal Control
Bilal Hammoud, Majid Khadiv, Ludovic Righetti
This paper addresses the problem of computing optimal impedance schedules for legged locomotion tasks involving complex contact interactions. We formulate the problem of impedance…
DeepQ Stepper: A framework for reactive dynamic walking on uneven terrain
Avadesh Meduri, Majid Khadiv, Ludovic Righetti
Reactive stepping and push recovery for biped robots is often restricted to flat terrains because of the difficulty in computing capture regions for nonlinear dynamic models. In th…
Efficient Multi-Contact Pattern Generation with Sequential Convex Approximations of the Centroidal Dynamics
Brahayam Ponton, Majid Khadiv, Avadesh Meduri +1
This paper investigates the problem of efficient computation of physically consistent multi-contact behaviors. Recent work showed that under mild assumptions, the problem could be…
Robot Learning with Crash Constraints
Alonso Marco, Dominik Baumann, Majid Khadiv +3
In the past decade, numerous machine learning algorithms have been shown to successfully learn optimal policies to control real robotic systems. However, it is common to encounter…
Variable Horizon MPC with Swing Foot Dynamics for Bipedal Walking Control
Elham Daneshmand, Majid Khadiv, Felix Grimminger +1
In this paper, we present a novel two-level variable Horizon Model Predictive Control (VH-MPC) framework for bipedal locomotion. In this framework, the higher level computes the la…
Robust walking based on MPC with viability guarantees
Mohammad Hasan Yeganegi, Majid Khadiv, Andrea Del Prete +2
Model predictive control (MPC) has shown great success for controlling complex systems such as legged robots. However, when closing the loop, the performance and feasibility of the…
TriFinger: An Open-Source Robot for Learning Dexterity
Manuel Wüthrich, Felix Widmaier, Felix Grimminger +12
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade. We argue that a hindrance is the high cost…
Stochastic and Robust MPC for Bipedal Locomotion: A Comparative Study on Robustness and Performance
Ahmad Gazar, Majid Khadiv, Andrea Del Prete +1
Linear Model Predictive Control (MPC) has been successfully used for generating feasible walking motions for humanoid robots. However, the effect of uncertainties on constraints sa…