A Set-Theoretic Approach to Multi-Task Execution and Prioritization
This work addresses the need for flexible and safe task prioritization in robotic systems, which is crucial for applications involving safety-critical operations, but it appears to be an incremental improvement over existing methods.
The paper tackles the problem of executing and prioritizing multiple tasks in robotics, particularly with time-varying priorities, by introducing an optimization-based framework using extended set-based tasks and control barrier functions, and demonstrates its application on a redundant robotic manipulator.
Executing multiple tasks concurrently is important in many robotic applications. Moreover, the prioritization of tasks is essential in applications where safety-critical tasks need to precede application-related objectives, in order to protect both the robot from its surroundings and vice versa. Furthermore, the possibility of switching the priority of tasks during their execution gives the robotic system the flexibility of changing its objectives over time. In this paper, we present an optimization-based task execution and prioritization framework that lends itself to the case of time-varying priorities as well as variable number of tasks. We introduce the concept of extended set-based tasks, encode them using control barrier functions, and execute them by means of a constrained-optimization problem, which can be efficiently solved in an online fashion. Finally, we show the application of the proposed approach to the case of a redundant robotic manipulator.