Examination Committee

Prof Ling SHI, ECE/HKUST (Chairperson)
Prof Chi Ying TSUI, ECE/HKUST (Thesis Supervisor)
Prof Ming LIU, ECE/HKUST
Prof Kam Tim WOO, ECE/HKUST
 
  

Abstract

Searching operation is one of the most common applications of robotics. Ability to operate continuously greatly influences the applicability of autonomous robots in searching operation.    This work proposes a design of swarm robotic system for long-term searching operations. Detailed specifications and the macroscopic behavior model are shown. A novel mechanism of adjusting task-charge ratio automatically is proposed. A searching algorithm based on the Particle Swarm Optimization is implemented in the simulation environment. Several sets of simulation experiments were then conducted. The experimental results justify the survivability and scalability of the proposed system. In every experiment, system energy level keeps relatively stable throughout the whole simulation. A modified version of Response Threshold Model is proposed for this system to adjust the task-charge ratio according to the environmental conditions adaptively. The simulation results show that the searching performance is better than the one using manually tuned parameters.