000198847 001__ 198847
000198847 005__ 20190812205757.0
000198847 037__ $$aCONF
000198847 245__ $$aNull space redundancy learning for a flexible surgical robot
000198847 269__ $$a2014
000198847 260__ $$c2014
000198847 336__ $$aConference Papers
000198847 520__ $$aA new challenge for surgical robotics is placed in the use of flexible manipulators, to perform procedures that are impossible for currently available rigid robots. Since the surgeon only controls the end-effector of the manipulator, new control strategies need to be developed to correctly move its flexible body without damaging the surrounding environment. This paper shows how a positional controller for a new surgical robot (STIFF-FLOP) can be learnt from the demonstrations given by an expert user. The proposed algorithm exploits the variability of the task to comply with the constraints only when needed, by implementing a minimal intervention principle control strategy. The results are applied to scenarios involving movements inside a constrained environment and disturbance rejection.
000198847 700__ $$aBruno, D.
000198847 700__ $$aCalinon, S.
000198847 700__ $$aCaldwell, D. G.
000198847 7112_ $$aProc. IEEE Intl Conf. on Robotics and Automation (ICRA)
000198847 8564_ $$zn/a$$yn/a$$uhttps://infoscience.epfl.ch/record/198847/files/Bruno_ICRA_2014.pdf$$s1082968
000198847 909C0 $$xU10381$$pLIDIAP$$0252189
000198847 909CO $$ooai:infoscience.tind.io:198847$$qGLOBAL_SET$$pconf$$pSTI
000198847 937__ $$aEPFL-CONF-198847
000198847 970__ $$aBruno_ICRA_2014/LIDIAP
000198847 973__ $$aEPFL
000198847 980__ $$aCONF