Phd Thesis

 

Title: "Genetic Algorithms in Robot Trajectory Planning" (1996).

University of Patras, School of Engineering, Mechanical Engineering Department, January 1996. Nemertes institutional repository of University of Patras (http://nemertes.lis.upatras.gr/jspui/handle/10889/4529).

 

Summary

The use of genetic algorithms (GAs) for the solution of motion planning of robotic systems which perform logistics operations within a flexible manufacturing system (FMS), as well as, logistics tasks in indoors hazardous environments was investigated. Robot motion planning (RMP) is a PSPACE-hard combinatorial problem loosely stated as: How can a robot decide what motions to perform in order to achieve desired tasks in its environment? A number of novel biological-inspired solution approaches were developed and evaluated on computer simulated environments, as well as, on real industrial environments. In comparison to existing RMP methods, the developed evolutionary-based approaches were found superior in terms of both solutions quality and speed of convergence. Furthermore, focusing on RMP of robot manipulators, the proposed approaches tackled with high success difficult kinematics problems such as: the inverse kinematics for robots with redundant degrees of freedom, the maximization of robot’s manipulability as well as the path following by the robot’s end-effector on demanded trajectories.