Dynamic multi-objective optimal task distribution for tele-operated mobile manipulators

Robots are developed to perform myriad kinds of complex tasks. To enhance the system performance, tasks should be optimally distributed among robots or subsystems of a single robot. Applied to mobile manipulators, optimal task distribution can be obtained by implementing an optimal redundancy resolution approach. A lot of work has been done in this area with a priori-specified tasks. However, for tele-operated mobile manipulator systems, tasks are generated on-line by the operator, and task requirements vary significantly and are not known a priori. This renders static task distribution schemes unsuitable for achieving optimal performance and mandates the use of online modification of optimal task distribution algorithms. This paper proposes a new optimal task distribution method for tele-operated mobile manipulators. In this method, task dexterity indices, which describe the task requirements are generated online. Based on these indices, the criterion function for optimal performance is constructed using physical programming. The solution obtained by this algorithm is more suitable for varying tasks, and has a better defined physical meaning. The effectiveness of the proposed method is verified by experimental results.