2 citations · 4 across the 7 of their papers we have counts for
9 papers
Cost Function Estimation Using Inverse Reinforcement Learning with Minimal Observations
Sarmad Mehrdad, Avadesh Meduri, Ludovic Righetti
We present an iterative inverse reinforcement learning algorithm to infer optimal cost functions in continuous spaces. Based on a popular maximum entropy criteria, our approach ite…
Diffusion-based learning of contact plans for agile locomotion
Victor Dhédin, Adithya Kumar Chinnakkonda Ravi, Armand Jordana +5
Legged robots have become capable of performing highly dynamic maneuvers in the past few years. However, agile locomotion in highly constrained environments such as stepping stones…
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…
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…
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…
Rapid Convex Optimization of Centroidal Dynamics using Block Coordinate Descent
Paarth Shah, Avadesh Meduri, Wolfgang Merkt +3
In this paper we explore the use of block coordinate descent (BCD) to optimize the centroidal momentum dynamics for dynamically consistent multi-contact behaviors. The centroidal d…