We consider the problem of impedance control for the physical interaction between the soft tip of a robot finger, where the nonlinear characteristics of the reproducing force and the finger dynamic parameters are unknown, and a rigid object or environment under kinematic uncertainties arising from both uncertain contact point location and uncertain rigid object geometry. An adaptive controller ...

In this paper, a disturbance observer (DOB) based predictive control approach is developed for the image-based visual servoing of an inertially stabilized platform (ISP). As limitation in degrees freedom two-axes ISP, it hard to estimate variable feature depth target at each cycle when using uncalibrated camera, which brings challenge design controller. To end, depth-independent kinematic matri...

We revisit the problem of revising probabilistic beliefs using uncertain evidence, and report results on four major issues relating to this problem: How to specify uncertain evidence? How to revise a distribution? Should, and do, iterated belief revisions commute? And how to provide guarantees on the amount of belief change induced by a revision? Our discussion is focused on two main methods fo...

ABSTRACT In this paper, a new kind of smooth time-varying controller was proposed for the robust stabilization problem of nonholonomic kinematics mobile robots with uncertain camera parameters based on visual feedback. And a torque controller was also designed by using the method of computed-torque for the dynamic model associated with uncertain disturbances. This torque controller can let the ...

In this paper, a method for solving forward and inverse kinematics of redundant manipulator is proposed. Obtaining the joint variables of these manipulators from a desired position of the robot end-effector called as inverse kinematics (IK), is one of the most important problems in robot kinematics and control. The difficulties in solving the IK equations of these redundant robot manipulator ar...

This paper presents a fully Bayesianway to solve the simultaneous localization and spatial prediction problemusing aGaussianMarkov randomfield (GMRF)model. The objective is to simultaneously localize robotic sensors and predict a spatial field of interest using sequentially collected noisy observations by robotic sensors. The set of observations consists of the observed noisy positions of robot...