Wang Zhong-min

Coverage path planning for mobile robot based on genetic algorithm

Environment modeling for mobile robot is built up by using Boustrophedon cell decomposition method, and each sub-region is set numbers and basis point based on the characteristics of modeling, and connectivity relations among all sub-regions are established. All sub-regions are encoded by genetic algorithm (GA), and information of basis points between the sub-regions and sub-regions inside are set up and also achieved by GA, the optimal coverage sequences are obtained with GA, and in each sub-region a partial coverage is realized in the form of reciprocating movement, then problem of complete coverage for mobile robot is changed into a traveling salesman problem (TSP). Finally, the relationships between parameters of GA and search abilities are deeply studied, then the best parameters of GA are obtained. Simulation results show the effectiveness of GA for mobile robots coverage path planning.

Trajectory tracking of a 6-DOF industrial manipulator

An algorithm that simulates the trajectories for a 6 -DOF articulate manipulator was proposed. A Fanuc-type 6-DOF industrial manipulator was first modeled in MATLAB, then using basic matrix computations, a simplified algorithm was developed which is capable of efficiently computing the trajectory of the known manipulator and a Guide User Interface (GUI) was developed to simulate the trajectory in MATLAB environment given the required inputs. The orientation and position parameters are required, and then the basic machine parameters like acceleration, velocity and time also were required. The algorithm was found to efficiently compute and simulate the trajectories for the manipulator given any two of the tree manipulator parameters and an approximate trajectory given any one of the three manipulator parameters.