The design of autonomous robots, able to closely cooperate with human users in shared tasks, provides many new challenges for robotics research. Compared to industrial applications, robots working in human environments will need to have human-like abilities in their cognitive and motor behaviors. Here we present a model for generating trajectories of a high degree of freedom robotics arm-hand system that reflects optimality principles of human motor control. The process of finding a human-like trajectory among all possible solutions is formalized as a large-scale nonlinear optimization problem. We compare numerically three existing solvers, IPOPT, KNITRO and SNOPT, in terms of their real-time performance in different reach-to-grasp problems that are part of a human-robot interaction task. The results show that the SQP methods obtain better results than the IP methods. SNOPT finds optimal solutions for all tested problems in competitive computational times, thus being the one that best serves our purpose. ; Eliana Costa e Silva was supported by FCT (grant: SFRH/BD/23821/2005). The resources and equipment were financed by FCT and UM through project "Anthropomorphic robotic systems: control based on the processing principles of the human and other primates motor system and potential applications in service robotics and biomedical engineering" (Ref. CONC-REEQ/17/2001) and by EC through project "JAST: Joint-Action Science and Technology" (Ref. IST- 2-003747-IP).We thank the Mobile and Anthropomorphic Robotics Laboratory at University of Minho for constant good work environment. Finally, we would like to thank Carl Laird and Andreas Wachter for making available IPOPT, and AMPL for making available an unrestricted 30 days trial version of AMPL, KNITRO and SNOPT executables.
Nonlinear optimization for human-like movements of a high degree of freedom robotics arm-hand system
2011-01-01
Conference paper
Electronic Resource
English
DDC: | 629 |
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