Title :
Hybrid learning control techniques for the manipulation of rigid objects
Author :
Aicardi, M. ; Cannata, G. ; Casalino, G.
Author_Institution :
Dept. of Commun. Comput. & Syst. Sci., Genova Univ., Italy
Abstract :
The problem of dexterous manipulation of rigid objects is discussed. A formalism suitable for representing the space of the contact forces allowing a grasped object to perform an assigned motion is presented. The advantages that can be gained using such a formalism when robust grasping planning problems are dealt with are highlighted. The question of how manipulation dexterity in performing grasping actions could be attained in cases where possible repetitions of the planned task are somehow allowed is discussed. This is done on the basis of results concerning the so-called iterative learning hybrid control theory, extended to address robotic manipulation problems
Keywords :
adaptive control; force control; learning (artificial intelligence); manipulators; path planning; dexterous manipulation; hybrid learning control techniques; iterative learning hybrid control theory; rigid objects; robotic manipulation; robust grasping planning problems; Automatic control; Automation; Communication system control; Contacts; Control theory; Councils; Force control; Motion control; Robots; Robust control;
Conference_Titel :
Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-8186-3450-2
DOI :
10.1109/ROBOT.1993.292056