Safety-Critical Control of Nonholonomic Vehicles in Dynamic Environments using Velocity Obstacles

This paper considers collision avoidance for vehicles with first-order nonholonomic constraints maintaining nonzero forward speeds, moving within dynamic environments. We leverage the concept of control barrier functions (CBFs) to synthesize control inputs that prioritize safety, where the safety criteria are derived from the velocity obstacle principle. Existing instantiations of CBFs for collision avoidance, e.g., based on maintaining a minimal distance, can result in control inputs that make the vehicle stop or even reverse. The proposed formulation effectively separates speed control from steering, allowing the vehicle to maintain a forward motion without compromising safety. This is beneficial for ensuring that the vehicle advances towards its desired destination, and it is moreover an underlying requirement for certain vehicles such as marine vessels and fixed-wing UAVs. Theoretical safety guarantees are provided, and numerical simulations demonstrate the efficiency of the strategy in environments containing moving obstacles.

Task-Priority Control of Redundant Robotic Systems using Control Lyapunov and Control Barrier Function based Quadratic Programs

Redundant robotic systems are designed to accomplish multiple tasks simultaneously. Tasks are functions of the system configuration, and can be divided into groups by their priority. System redundancy can be exploited by including lower-priority optimization tasks within the control framework. However, it is important that the inclusion of such lower-priority tasks does not have an effect on higher-priority safety-related and operational tasks. This paper presents a novel task-priority framework 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. Simulation results of a hyper-redundant articulated intervention autonomous underwater vehicle (AIAUV) is presented to validate the proposed framework.