Complementary data fusion in guidance and control of robot compliant motion

This paper is devoted to the control problem of a robot manipulator for a class of constrained motions in an unknown environment. To accomplish a task in the presence of uncertainties, we propose a new guidance and control strategy based on multisensor fusion. Three different sensors-robot joint encoders, a wrist force-torque sensor and a vision system-are utilized for our task. First of all, a sensor-based hybrid position/force control scheme is proposed for an unknown contact surface. Secondly, a new multisensor fusion scheme is utilized to handle an uncalibrated workcell, wherein the surface on which there is a path to be followed by a robot is assumed to be unknown but visible by the vision system and the precise position and orientation of camera(s) with respect to the base frame of the robot is also assumed to be unknown. Our work is related with areas such as visual servoing, multisensor fusion and robot control for constrained motion. The main features of the proposed approach are: (i) multi-sensor fusion is used both for two disparate sensors (i.e. force-torque and visual sensors) and for complementary observed data rather than redundant ones as in traditional way; (ii) visual servoing is realized on the tangent space of the unknown surface; (iii) calibration of the camera with respect to the robot is not needed.