Hand-eye-vision based control for an inspection robot's autonomous line grasping

In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.

Grasping Force Planning and Control for Tendon-driven Anthropomorphic Prosthetic Hands

A force planning and control method is proposed for a tendon-driven anthropomorphic prosthetic hand. It is necessary to consider grasping stability for the anthropomorphic prosthetic hand with multi degrees of freedom which aims to mimic human hands with dexterity and stability. The excellent grasping performance of the anthropomorphic prosthetic hand mainly depends on the accurate computation of the space position of finger tips and an appropriate grasping force planning strategy. After the dynamics model of the tendon-driven anthropomorphic prosthetic hand is built, the space positions of the finger tips are calculated in real time by solving the dynamic equations based on the Newton iteration algorithm with sufficient accuracy. Then, the balance of internal grasping force on the thumb is adopted instead of force closure of the grasped objects to plan the grasping forces of other fingers based on the method of the linear constraint gradient flow in real time. Finally, a fuzzy logic controller is used to control the grasping force of the prosthetic hand. The proposed force planning and control method is implemented on the tendon-driven anthropomorphic prosthetic hand and the experimental results dem- onstrate the feasibility and effectiveness of the proposed method.