Title :
iTASC: a tool for multi-sensor integration in robot manipulation
Author :
Smits, Ruben ; De Laet, Tinne ; Claes, Kasper ; Bruyninckx, Herman ; De Schutter, Joris
Author_Institution :
Dept. of Mech. Eng., Katholieke Univ. Leuven, Leuven
Abstract :
iTASC (acronym for dasiainstantaneous task specification and controlpsila) by J. De Schutter (2007) is a systematic constraint-based approach to specify complex tasks of general sensor-based robot systems. iTASC integrates both instantaneous task specification and estimation of geometric uncertainty in a unified framework. Automatic derivation of controller and estimator equations follows from a geometric task model that is obtained using a systematic task modeling procedure. The approach applies to a large variety of robot systems (mobile robots, multiple robot systems, dynamic human-robot interaction, etc.), various sensor systems, and different robot tasks. Using an example task, this paper shows that iTASC is a powerful tool for multi-sensor integration in robot manipulation. The example task includes multiple sensors: encoders, a force sensor, cameras, a laser distance sensor and a laser scanner. The paper details the systematic modeling procedure for the example task and elaborates on the task specific choice of two types of task coordinates: feature coordinates, defined with respect to object and feature frames, which facilitate the task specification, and uncertainty coordinates to model geometric uncertainty. Experimental results for the example task are presented.
Keywords :
manipulators; multi-robot systems; robot programming; sensor fusion; cameras; constraint-based approach; encoder; force sensor; geometric uncertainty estimation; iTASC; instantaneous task specification and control; laser distance sensor; laser scanner; multisensor integration; robot manipulation; sensor-based robot system; Automatic control; Human robot interaction; Laser modes; Mobile robots; Power system modeling; Robot kinematics; Robot sensing systems; Robotics and automation; Solid modeling; Uncertainty;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 2008. MFI 2008. IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-2143-5
Electronic_ISBN :
978-1-4244-2144-2
DOI :
10.1109/MFI.2008.4648032