Inverse kinematics algorithms are commonly used in robotic systems to transform tasks to joint references, and several methods exist to ensure the achievement of several tasks simultaneously. The multiple task-priority inverse kinematics framework allows tasks to be considered in a prioritized order by projecting task velocities through the null spaces of higher-priority tasks. This paper extends this framework to handle set-based tasks, i.e., tasks with a range of valid values, in addition to equality tasks, which have a specific desired value. Examples of set-based tasks are joint limit and obstacle avoidance. The proposed method is proven to ensure asymptotic convergence of the equality task errors and the satisfaction of all high-priority set-based tasks. The practical implementation of the proposed algorithm is discussed, and experimental results are presented where a number of both set-based and equality tasks have been implemented on a 6 degree of freedom UR5, which is an industrial robotic arm from Universal Robots. The experiments validate the theoretical results and confirm the effectiveness of the proposed approach.
Abstract-Inverse kinematics algorithms are commonly used in robotic systems to achieve desired behavior, and several methods exist to ensure the achievement of numerous tasks simultaneously. The multiple task-priority inverse kinematics framework allows a consideration of tasks in a prioritized order by projecting task velocities through the null-spaces of higher priority tasks. Recent results have extended this framework from equality tasks to also handling set-based tasks, i.e. tasks that have an interval of valid values. The purpose of this paper is to further investigate and experimentally validate this algorithm and its properties. In particular, this paper presents experimental results where a number of both set-based and equality tasks have been implemented on the 6 Degree of Freedom UR5 which is an industrial robotic arm from Universal Robots. The experiments validate the theoretical results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.