activity
20192025
most citedBiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning

5 citations · 12 across the 11 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

cs.RO2022★ 2 cited

Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion

Victor Dhédin, Haolong Li, Shahram Khorshidi +8

Implementing dynamic locomotion behaviors on legged robots requires a high-quality state estimation module. Especially when the motion includes flight phases, state-of-the-art appr…

cs.RO2022

MPC with Sensor-Based Online Cost Adaptation

Avadesh Meduri, Huaijiang Zhu, Armand Jordana +1

Model predictive control is a powerful tool to generate complex motions for robots. However, it often requires solving non-convex problems online to produce rich behaviors, which i…

cs.RO2022★ 3 cited

ContactNet: Online Multi-Contact Planning for Acyclic Legged Robot Locomotion

Angelo Bratta, Avadesh Meduri, Michele Focchi +2

In legged logomotion, online trajectory optimization techniques generally depend on heuristic-based contact planners in order to have low computation times and achieve high replann…

cs.RO2022

Efficient Object Manipulation Planning with Monte Carlo Tree Search

Huaijiang Zhu, Avadesh Meduri, Ludovic Righetti

This paper presents an efficient approach to object manipulation planning using Monte Carlo Tree Search (MCTS) to find contact sequences and an efficient ADMM-based trajectory opti…

cs.RO2022★ 1 cited

ValueNetQP: Learned one-step optimal control for legged locomotion

Julian Viereck, Avadesh Meduri, Ludovic Righetti

Optimal control is a successful approach to generate motions for complex robots, in particular for legged locomotion. However, these techniques are often too slow to run in real ti…

cs.RO2022★ 5 cited

BiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning

Avadesh Meduri, Paarth Shah, Julian Viereck +3

Online planning of whole-body motions for legged robots is challenging due to the inherent nonlinearity in the robot dynamics. In this work, we propose a nonlinear MPC framework, t…