Author Description

Automated materials-handling systems, such as Automated Guided Vehicles (AGVs), are currently designed to follow predefined paths. Thus, their autonomy and efficiency can be enhanced if they could make on-line routing decisions. The objective of this thesis is to develop a novel on-line trajectory-planning method for fast robotic interception of moving objects in the presence of moving obstacles.The proposed trajectory planner is a hybrid system that augments the Proportional Navigation (PN) guidance law with a Modified Exact Cell Decomposition (MECD) obstacle avoidance method. It is implemented in both computer simulations and experimentation. The performance was evaluated against the performance of conventional Cell Decomposition methods. The results show that the proposed hybrid trajectory planner is able to achieve tangibly faster interceptions.