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Set-Based Tasks within the Singularity-Robust Multiple Task-Priority Inverse Kinematics Framework: General Formulation, Stability Analysis, and Experimental Results

Signe Moe, Gianluca Antonelli, Andrew R. Teel, Kristin Y. Pettersen, Johannes Schrimpf

发表年份
2016
引用次数
100
访问权限
开放获取

摘要

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.

关键词

Inverse kinematicsComputer scienceSet (abstract data type)Task (project management)KinematicsStability (learning theory)Convergence (economics)RobotForward kinematicsArtificial intelligence

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