Assessment and Future Directions of Nonlinear Model Predictive ...

An Experimental Study of Stabilizing RecedingHorizon Control of Visual Feedback System withPlanar ManipulatorsMasayuki Fujita, Toshiyuki Murao, Yasunori Kawai, and Yujiro NakasoDepartment of Mechanical and Control Engineering, Tokyo Institute of Technology,2-12-1 S5-26 O-okayama Meguro-ku, Tokyo 152-8552, Japanfujita@ctrl.titech.ac.jpSummary. This paper investigates vision based robot control based on a recedinghorizon control strategy. The stability of the receding horizon control scheme is guaranteedby using the terminal cost derived from an energy function of the visual feedbacksystem. By applying the proposed control scheme to a two-link direct drive manipulatorwith a CCD camera, it is shown that the stabilizing receding horizon control nicelyworks for a planar visual feedback system. Furthermore, actual nonlinear experimentalresults are assessed with respect to the stability and the performance.1 IntroductionRobotics and intelligent machines need sensory information to behave autonomouslyin dynamical environments. Visual information is particularly suitedto recognize unknown surroundings. In this sense, vision is one of the highestsensing modalities that currently exist. Vision based control of robotic systemsinvolves the fusion of robot kinematics, dynamics, and computer vision to controlthe motion of the robot in an efficient manner. The combination of mechanicalcontrol with visual information, so-called visual feedback control or visual servoing,is important when we consider a mechanical system working in dynamicalenvironments [1].In previous works, Kelly [2] considered the set-point problem with a static targetfor a dynamic visual feedback system that includes the manipulator dynamicswhich is not be negligible for high speed tasks. The authors discussed passivitybased control of the eye-in-hand system [3, 4]. However, the control law proposedin [3] is not based on optimization, the desired control performance cannot beguaranteed explicitly.Receding horizon control, also recognized as model predictive control is awell-known control strategy in which the current control action is computed bysolving, a finite horizon optimal control problem on-line [5]. A large number ofindustrial applications using model predictive control can be found in chemicalindustries where the processes have relatively slow dynamics. On the contrary, fornonlinear and relatively fast systems such as in robotics, few implementationsof the receding horizon control have been reported. For the receding horizoncontrol, many researchers have tackled the problem of stability guarantees. AnR. Findeisen et al. (Eds.): Assessment and Future Directions, LNCIS 358, pp. 573–580, 2007.springerlink.com c○ Springer-Verlag Berlin Heidelberg 2007