Anthropomorphic Robotic: Hand to Grasp Object Method


Anthropomorphic robotic is a new approach towards the data collection by hand to grasp the object method and which is developed by researchers at FZI, Germany.

The robotic arm consists of a device that helps to understand the object while touching and it grasps the basic information. This is similar to the human nervous system and the robot can easily identify the through a touch. The soft grasping capability enables the ability of the robot to work in a complex environment and helps to understand the situations. It consists of an internal part named Primitives, which controls the entire system while performing a task.

The Anthropomorphic robotic works on the principles of the biological phenomenon and it helps to control the motor. The involvement of biological phenomenon improves the quality of adaptively, compliant control, and event-based problem-solving. The spiking neuron model is the major part of the anthropomorphic robotic and is the same as the human brain. It consists of four main components such as affordance activation, finger primitives, reflexes, and hand primitives.  The affordance activation is a mechanism that deals with the pattern of the hand. Finger primitives as like a finger function in a human body and which deal with closer actions. Hand primitives deal with the coordination with the affordances and the finger. Reflexes are in two types, one deals with the moment of the finger and the other involves the compliant controller.

To develop complex grasping behavior, the spiking neural network combines two control loops. Each loop deals with a certain element to improve the quality of the behavior. The main objective is the grasping an object by the finger using control of force. The complete operation is very complex and the entire device is related to each other. The robotic has a hierarchy arrangement for the control of each system. By using the approach, the researchers identify the possibility of the model cylinder, sphere, and pinch grasping techniques. The technique is good enough to perform accurately in complex work environments. As per the grasping information, the Anthropomorphic robotic improve their involvement and control the process. So the implementation of the robotic improves the quality of work and minimizes errors also.


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