Adaptive CLF-MPC With Application To Quadrupedal Robots

Abstract

Modern robotic systems are endowed with superior mobility and mechanical skills that make them suited to be employed in real-world scenarios, where interactions with heavy objects and precise manipulation capabilities are required. For instance, legged robots with high payload capacity can be used in disaster scenarios to remove dangerous material or carry injured people. It is thus essential to develop planning algorithms that can enable complex robots to perform motion and manipulation tasks accurately. In addition, online adaptation mechanisms with respect to new, unknown environments are needed. In this work, we impose that the optimal state-input trajectories generated by Model Predictive Control (MPC) satisfy the Lyapunov function criterion derived in adaptive control for robotic systems. As a result, we combine the stability guarantees provided by Control Lyapunov Functions (CLFs) and the optimality offered by MPC in a unified adaptive framework, yielding an improved performance during the robot's interaction with unknown objects. We validate the proposed approach in simulation and hardware tests on a quadrupedal robot carrying un-modeled payloads and pulling heavy boxes.

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Cited by in corpus (9)

• Adaptive Force-Based Control of Dynamic Legged Locomotion over Uneven Terrain
• Adaptive Non-linear Centroidal MPC with Stability Guarantees for Robust Locomotion of Legged Robots
• Hierarchical Quality-Diversity for Online Damage Recovery
• Optimization-Based Reference Generator for Nonlinear Model Predictive Control of Legged Robots
• Predictive Control with Indirect Adaptive Laws for Payload Transportation by Quadrupedal Robots
• PACC: A Passive-Arm Approach for High-Payload Collaborative Carrying with Quadruped Robots Using Model Predictive Control
• Online Non-linear Centroidal MPC for Humanoid Robots Payload Carrying with Contact-Stable Force Parametrization
• Harnessing Natural Oscillations for High-Speed, Efficient Asymmetrical Locomotion in Quadrupedal Robots
• Torque-Minimizing Control Allocation for Overactuated Quadrupedal Locomotion