The paper discusses the challenges of optimizing the cost function parameters of Model Predictive Control (MPC) for autonomous vehicles. The authors propose using Reinforcement Learning (RL) to learn optimal parameter…
Continue readingThis paper addresses the challenge of controlling a drone in unknown dynamic environments using a new model predictive control (MPC) approach called hyMPC. The hyMPC leverages high-level decision variables to…
Continue readingThe article introduces a new online model-predictive trajectory planner for robotic manipulators, called BoundMPC. This planner allows robots to follow collision-free Cartesian reference paths in dynamic environments. The unique feature…
Continue readingThe paper presents BoundMPC, a novel online model-predictive trajectory planner for robotic manipulators. This planner allows the collision-free following of Cartesian reference paths in the end-effector’s position and orientation, including…
Continue readingThis research paper proposes an efficient model predictive control (MPC) strategy for autonomous miniature racing. It uses a feasible sequential quadratic programming (SQP) algorithm to generate intermediate iterations, which allows…
Continue readingThe paper discusses a method for controlling autonomous docking tasks of a personal mobility vehicle. The authors propose a non-linear model predictive control (NMPC) based visual servoing technique, which uses…
Continue readingThe paper discusses the development of a soft-constrained iterative linear quadratic regulator (soft-CILQR) algorithm for autonomous vehicle applications. The algorithm integrates the CILQR algorithm and a model predictive control constraint…
Continue readingThis research focuses on the challenges faced by autonomous vehicles traversing uneven terrain at high speeds. The study introduces a physics-based framework for identifying traversability constraints and mitigating risks such…
Continue readingThe article discusses SICNav, a method for safe and interactive crowd navigation for robots. The system uses Model Predictive Control (MPC) to predict and react to human movements, avoiding collisions….
Continue readingThis research focuses on trajectory optimization for bipedal locomotion, specifically in scenarios where the robot encounters unforeseen external perturbations. The work presents a task and motion planning framework that generates…
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