100 citations · 100 across the 7 of their papers we have counts for
9 papers
Where Small Mistakes Matter: Quantifying State Criticality for Imitation Learning
Yusuf Umut Ciftci, Joonwon Kang, Ajay Suresha Sathya +1
Imitation learning typically treats every demonstration state as equally important, optimizing a behavior-cloning objective uniformly across the dataset. Yet not all states are cre…
OTRetarget: Joint Robot and Object Motion Retargeting via Optimal Transport
Guillaume Besset, Erwann Carn, Timothée Carecchio +5
Transferring human motion to humanoid robots requires adapting the demonstrated motion to the robot morphology while preserving interactions with the environment. This is particula…
Infeasible optimization problems and the hierarchical augmented Lagrangian method in imitation learning
Roland Andrews, Justin Carpentier, Ajay Sathya
Imitation learning (IL) is an effective approach to train complex robotics policies. Recent works have introduced hard constraints into imitation-learning optimization problems to…
Constrained Dynamics Simulation: More With Less
Ajay Suresha Sathya
Efficient robot dynamics simulation is a fundamental problem key for robot control, identification, design and analysis. This research statement explores my current progress in thi…
PV-OSIMr: A Lowest Order Complexity Algorithm for Computing the Delassus Matrix
Ajay Suresha Sathya, Wilm Decre, Jan Swevers
We present PV-OSIMr, an efficient algorithm for computing the Delassus matrix (also known as the inverse operational space inertia matrix) for a kinematic tree, with the lowest ord…
Efficient Constrained Dynamics Algorithms based on an Equivalent LQR Formulation using Gauss' Principle of Least Constraint
Ajay Suresha Sathya, Herman Bruyninckx, Wilm Decre +1
We derive a family of efficient constrained dynamics algorithms by formulating an equivalent linear quadratic regulator (LQR) problem using Gauss principle of least constraint and…
FATROP : A Fast Constrained Optimal Control Problem Solver for Robot Trajectory Optimization and Control
Lander Vanroye, Ajay Sathya, Joris De Schutter +1
Trajectory optimization is a powerful tool for robot motion planning and control. State-of-the-art general-purpose nonlinear programming solvers are versatile, handle constraints e…
Safe-Planner: A Single-Outcome Replanner for Computing Strong Cyclic Policies in Fully Observable Non-Deterministic Domains
Vahid Mokhtari, Ajay Suresha Sathya, Nikolaos Tsiogkas +1
Replanners are efficient methods for solving non-deterministic planning problems. Despite showing good scalability, existing replanners often fail to solve problems involving a lar…
Embedded nonlinear model predictive control for obstacle avoidance using PANOC
Ajay Sathya, Pantelis Sopasakis, Ruben Van Parys +3
We employ the proximal averaged Newton-type method for optimal control (PANOC) to solve obstacle avoidance problems in real time. We introduce a novel modeling framework for obstac…