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This paper presents the architecture of autonomous material handling vehicles. The centralized coordination of multiple vehicles and three-layer architecture (deliberative, sequencing, and reflexive layers) are adopted. The navigation controls, including configuration control, visual servoing, path tracking, and collision avoidance, are developed. The finite state machine (FSM) that supervises the control modules to complete the material handling task is elucidated. The experimental results of a forklift transporting a pallet from an initial to a desired goal configuration are demonstrated.

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This paper discusses a particle swarm optimization (PSO)-based motion-planning algorithm in a multiple-vehicle system that minimizes the traveling time of the slowest vehicle by considering, as constraints, the radial and tangential accelerations and maximum linear velocities of all vehicles. A class of continuous-curvature three-degree Bezier curves are selected as the basic shape of the vehicle trajectories to minimize the number of parameters required to express them mathematically. In addition, velocity profile generation using the local minimum of the radial-accelerated linear velocity profile, which reduces the calculation effort, is introduced. A new PSO-based search algorithm, called "particle-group-based PSO," is introduced to find the best combination of trajectories that minimizes the traveling time of the slowest vehicle. A particle group is designed to wrap up a set of particles representing each vehicle. The first and last two control points characterizing a curve are used as the state vector of a particle. Simulation results demonstrating the performance of the proposed method are presented. The main advantage of the proposed method is its minimization of the velocity-profile-generation time, and thereby, its maximization of the search time.

A multi-objective distribution routing algorithm by using modified Clarke and Wright Saving algorithm is presented. The problem to solve is to deliver loads to a number of outlets based load requirement. The objective function to minimize is the distance saving and traveling time of the resulted route started from depot to the outlets and return to the original depot. Problem to solve is generating a distribution route in a week considering traffic condition for each day. The original Clarke and Wright saving algorithm is modified such that the resulted routes (from a depot to some outlets) accommodates some constraints such as the maximum allowable traveling time, maximum number of delivery shifts, and maximum number of vehicles. The algorithm is applied to a distributor company with nine outlets, two vehicles, and two delivery shifts. In addition, the traffic condition on the outlet-to-outlet and the depot-to-outlet routes is considered. The simulation of the proposed algorithm shows that the algorithm can generate routes that comply with shift’s maximum delivery time and the vehicles’ capacities.