Task-Priority Control of Redundant Robotic Systems using Control Lyapunov and Control Barrier Function based Quadratic Programs
This work addresses control challenges for redundant robotic systems, offering a holistic approach that integrates redundancy resolution, dynamic control, and control allocation, though it appears incremental as it builds on existing CLF/CBF methods.
The paper tackles the problem of task-priority control for redundant robotic systems by proposing a novel framework based on control Lyapunov and barrier functions with quadratic programs, which guarantees strict priority among tasks and is validated through simulations of an autonomous underwater vehicle.
This paper presents a novel task-priority control framework for redundant robotic systems based on a hierarchy of control Lyapunov function (CLF) and control barrier function (CBF) based quadratic programs (QPs). The proposed method guarantees strict priority among different groups of tasks such as safety-related, operational and optimization tasks. Moreover, a soft priority measure in the form of penalty parameters can be employed to prioritize tasks at the same priority level. As opposed to kinematic control schemes, the proposed framework is a holistic approach to control of redundant robotic systems, which solves the redundancy resolution, dynamic control and control allocation problems simultaneously. Numerical simulations of a hyper-redundant articulated intervention autonomous underwater vehicle (AIAUV) is presented to validate the proposed framework.