Sensor Integration and Fusion for Autonomous Screwing Task by Dual-Manipulator Hand Robot

摘要

Sensing and manipulation of small objects are among the most challenging, requiring a very high degree of coordinated actuation in producing assembly work robots. It is inevitable for the development of a robot that is designed to execute complex tasks to apply multiple sensors for determination of a target's attributes. In this study, a seven-link dual-arm robot with three-fingered hands that exhibits human-like skills to manipulate small parts like nuts and bolts is proposed. The dynamical system of the robot requires attention in many aspects including control, sensor integration, image processing and trajectory planning strategies for small object manipulation. In this paper, the implementation of sensor integration between force and vision sensors for real-time autonomous grasping and screwing of an M10 nut and bolt by the robot is discussed. The measured data on the object or environment is used to create the robot's trajectory in real-time operation and to ensure safety of the robot. The proposed method applies a visual servoing structure for the recognition by camera, and impedance control for the hand robot to produce softness to the fingers. The required kinematics adjustments to modify the trajectories of arms and the robot hand's configuration are applied according to the measured data by the sensors. Experimental results indicate the performance of the proposed method in achieving the sensor-based planning and control for fully autonomous screwing task in real-time experiments. This shows the capability of the dual-manipulator hand robot for manipulating small objects and its applicability for more complex assembly tasks in the future.