title: A multi-sensorial hybrid control for robotic manipulation in human-robot workspaces.
abstract: Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach.
authors.affiliation: Department of Physics, System Engineering and Signal Theory, University of Alicante, San Vicente del Raspeig, Alicante 03690, Spain. jpomares@ua.es
authors.forename: Jorge
authors.initials: J
authors.lastname: Pomares
authors.forename: Ivan
authors.initials: I
authors.lastname: Perea
authors.forename: Gabriel J
authors.initials: GJ
authors.lastname: García
authors.forename: Carlos A
authors.initials: CA
authors.lastname: Jara
authors.forename: Juan A
authors.initials: JA
authors.lastname: Corrales
authors.forename: Fernando
authors.initials: F
authors.lastname: Torres
mesh_terms: D000465:Algorithms; D005385:Fingers; D006801:Humans; D008328:Man-Machine Systems; D012371:Robotics / Q000295:instrumentation* / Q000379:methods*; D013647:Task Performance and Analysis; D019415:Torque; D014110:Touch / Q000502:physiology; D014785:Vision, Ocular