4 papers
Accelerating and Scaling MPC-Guided Reinforcement Learning for Humanoid Locomotion and Manipulation
Junheng Li, Liang Wu, Sergio A. Esteban +3
In humanoid motion control, model predictive control (MPC) offers physically grounded prediction and constraint handling, while reinforcement learning (RL) enables robust whole-bod…
IKSPARK: Obstacle-Aware Inverse Kinematics via Convex Optimization
Liangting Wu, Roberto Tron
Inverse kinematics (IK) is central to robot control and motion planning, yet its nonlinear kinematic mapping makes it inherently nonconvex and particularly challenging under comple…
Koopman-Based Linear MPC for Safe Control using Control Barrier Functions
Shuo Liu, Liang Wu, Dawei Zhang +2
This paper proposes a Koopman-based linear model predictive control (LMPC) framework for safety-critical control of nonlinear discrete-time systems. Existing MPC formulations based…
Certifiably Optimal Estimation and Calibration in Robotics via Trace-Constrained Semi-Definite Programming
Liangting Wu, Roberto Tron
Many nonconvex problems in robotics can be relaxed into convex formulations via Semi-Definite Programming (SDP) that can be solved to global optimality. The practical quality of th…