首页|Virginia Polytechnic Institute and State University (Virginia Tech) Researcher D escribes Research in Robotics (A Distributed Layered Planning and Control Algori thm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear MPC Approach)

Virginia Polytechnic Institute and State University (Virginia Tech) Researcher D escribes Research in Robotics (A Distributed Layered Planning and Control Algori thm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear MPC Approach)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on robotics have been presented. Ac cording to news originating from Virginia Polytechnic Institute and State Univer sity (Virginia Tech) by NewsRx correspondents, research stated, “This paper aims to develop a distributed layered control framework for the navigation, planning , and control of multi-agent quadrupedal robots subject to environments with unc ertain obstacles and various disturbances.” The news journalists obtained a quote from the research from Virginia Polytechni c Institute and State University (Virginia Tech): “At the highest layer of the p roposed layered control, a reference path for all agents is calculated, consider ing artificial potential fields under a priori known obstacles. Secondly, in the middle layer, we employ a distributed nonlinear model predictive control (NMPC) scheme with a one-step delay communication protocol subject to reduced-order an d linear inverted pendulum (LIP) models of agents to ensure the feasibility of t he gaits and collision avoidance, addressing the degree of uncertainty in real-t ime. Finally, low-level nonlinear whole-body controllers (WBCs) impose the full- order locomotion models of agents to track the optimal and reduced-order traject ories. The proposed controller is validated for effectiveness and robustness on up to four A1 quadrupedal robots in simulations and two robots in the experiment s.”

Virginia Polytechnic Institute and State University (Virginia Tech)AlgorithmsEmerging TechnologiesMachine LearningNano-robotRobotics

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.14)