Study of the Non-Dominated Sorting Genetic Algorithm for the Optimal Structural Parameter of the Tooth-Arrangement Multi-Fingered Dextrous Hand

Firstly, the structural parameter optimization of the tooth-arrangement multi-fingered dextrous hand is studied. Secondly, as to the shortcomings that the Pareto solution of multi-objective optimization was distributed unevenly in NSGA-II, a non-dominated sorting genetic algorithm based on immune principle is proposed. Lastly, the structural parameter of the medical tooth-arrangement multi-fingered dextrous hand is optimized using the proposed algorithm. The experimental results show that this algorithm can optimize structural parameter of tooth-arrangement multi-fingered dextrous hand very well.

A Neurofuzzy Knowledge Based Architecture for Robotic Hand Manipulation Forces Learning

Optimal distribution of forces for manipulation by a robot hand, is a hard computational issue, specifically once a whole hand grasp is needed. It becomes a complicated issue, once a robotic hand is equipped with human like deformable sensory touching materials. For computing optimal set of manipulation forces, grip transform and inverse hand Jacobian play major roles for such purposes. This manuscript is discussing a Neurofuzzy learning technique for learning optimal force distribution by a dextrous hand. For learning purposes, optimal set of forces patterns were gathered in advanced using optimization formulation technique. After that, to let a Neurofuzzy system to learn the nonlinear kinematics-dynamics relations needed for force distribution. This is done by considering the computational requirements for the inverse hand Jacobian, in addition to the interaction between hand fingers and the object. Training patterns clustering, and generation of the fuzzy initial memberships, and updated shape of memberships, are considered as vital information to build upon for more reasoning of fuzzy interrelation. The technique is novel in a sense, that the adopted Neurofuzzy architecture was transparent in terms of revealing the learned hand optimal forces if then rules.

Analysis of the Grasp Planning Method for Manipulation of BH-4 Dextrous Hand

The paper presents method for planning robotic dexterous hand grasping task using example of the Beihang University’s BH-4 dexterous hand. The grasping planning method is devised through modeling and simulation and experimentally verified using physical prototype. The paper presents the method for forward and inverse kinematic solutions of the BH-4 robot 4-DOF finger, including transformation matrix between the palm coordinate system and the finger base coordinate system. In addition, the method of the idiographic manipulation is presented using example of ball grasping. The simulation results and physical experiment verify that the inverse kinematic solution is correct, and kinematic grasping and operating planning is valid and feasible. Finally, the experiment with the complex system integrated robot arm with dexterous hand is carried out. Experimental result shows that the more complicated grasping task can be done by a dexterous hand integrated in the robot arm system.