In this paper we develop an algorithm to modify the trajectories of multiple robots in cooperative manipulation. If a given trajectory results in joint torques which exceed the admissible torque range for one or more joints, the algorithm slows down or speeds up the trajectory so as to maintain all the torques within the admissible boundary. Our trajectory modification algorithm uses the concept of time scaling developed by Hollerbach[10] for single robots. A multiple robot system in cooperative manipulation has significantly different dynamics compared to single robot dynamics. As a result, time scaling algorithm for single robots is not usable with multi-robot system. The trajectory scaling schemes described in this paper requires the use of linear programming techniques and is designed to accommodate the internal force constraints and payload distribution strategies. As the multi-robot system is usually redundantly actuated, the actuator torques may be found from the quadratic minimization which has the effect of lowering energy consumption for the trajectory. A scheme for generating a robust multi-robot trajectories when the carried load mass and inertia matrix are unknown but vary within a certain range is also described in this paper. Several examples are given to show the effectiveness o f our multi-robot trajectory sealing scheme.
In this paper we describe a methodology to determine the time-optimal trajectories for cooperative multimanipulator systems (CMMS). The dynamics of CMMS and the joint torque constraints and the constraints on the intemal forces and the distribution of the payload are incorporated into our algorithm. Linear programming techniques are utilized to find the admissible phase plane boundary. Once the admissible phase plane region is found, the actual CMMS time-optimal trajectory can be constructed by employing similar approach used in single robot minimum time trajectory planning techniques. The minimum-time trajectories which are obtained from our algorithm, for a fixed path, result in trajectories which do not apply excessive forces on the manipulated object.
In this paper we develop an algorithm to modify the trajectories of multiple robots in cooperative manipulation. If a given trajectory results in joint torques which exceed the admissible torque range for one or more joints, the algorithm slows down or speeds up the trajectory so as to maintain all the torques within the admissible boundary. Our trajectory modification algorithm uses the concept of time scaling developed by Hollerbach[10] for single robots. A multiple robot system in cooperative manipulation has significantly different dynamics compared to single robot dynamics. As a result, time scaling algorithm for single robots is not usable with multi-robot system. The trajectory scaling schemes described in this paper requires the use of linear programming techniques and is designed to accommodate the internal force constraints and payload distribution strategies. As the multi-robot system is usually redundantly actuated, the actuator torques may be found from the quadratic minimization which has the effect of lowering energy consumption for the trajectory. A scheme for generating a robust multi-robot trajectories when the carried load mass and inertia matrix are unknown but vary within a certain range is also described in this paper. Several examples are given to show the effectiveness o f our multi-robot trajectory sealing scheme.
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.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.