115 citations · 258 across the 13 of their papers we have counts for
19 papers
Whole-Body MPC and Dynamic Occlusion Avoidance: A Maximum Likelihood Visibility Approach
Ibrahim Ibrahim, Farbod Farshidian, Jan Preisig +3
This paper introduces a novel approach for whole-body motion planning and dynamic occlusion avoidance. The proposed approach reformulates the visibility constraint as a likelihood…
A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation
Jia-Ruei Chiu, Jean-Pierre Sleiman, Mayank Mittal +2
In this paper, we present a real-time whole-body planner for collision-free legged mobile manipulation. We enforce both self-collision and environment-collision avoidance as soft c…
Combining Learning-based Locomotion Policy with Model-based Manipulation for Legged Mobile Manipulators
Yuntao Ma, Farbod Farshidian, Takahiro Miki +2
Deep reinforcement learning produces robust locomotion policies for legged robots over challenging terrains. To date, few studies have leveraged model-based methods to combine thes…
Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks
Maria Vittoria Minniti, Ruben Grandia, Kevin Fäh +2
Modern, torque-controlled service robots can regulate contact forces when interacting with their environment. Model Predictive Control (MPC) is a powerful method to solve the under…
Combined Sampling and Optimization Based Planning for Legged-Wheeled Robots
Edo Jelavic, Farbod Farshidian, Marco Hutter
Planning for legged-wheeled machines is typically done using trajectory optimization because of many degrees of freedom, thus rendering legged-wheeled planners prone to falling pre…
Collision-Free MPC for Legged Robots in Static and Dynamic Scenes
Magnus Gaertner, Marko Bjelonic, Farbod Farshidian +1
We present a model predictive controller (MPC) that automatically discovers collision-free locomotion while simultaneously taking into account the system dynamics, friction constra…