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Control Architecture of an Autonomous Material Handling Vehicle
In this paper, a control architecture that integrates path planning and motion control of an autonomous material handling vehicle is proposed. The three-layer architecture (deliberative, sequencing, and reflexive layers) is adopted. The deliberative layer plans a series of control actions for accomplishing tasks, the sequencing layer regulates the sequence of control modules and supervises the change of plan, and the reflexive layer collects sensory data and controls a specific motion. The control algorithms, which are derived considering sensor, environment, and kinematic constraints of the autonomous vehicle, assure the robustness against uncertainties as well as the safety during the motion. A finite state machine (FSM) that regulates the excecution of the planning and various control algorithms is proposed. The experimental results of a forklift transporting a pallet from an initial to a desired goal configuration demonstrate the effectiveness of the proposed control architecture.
Autonomous vehicle, forklift, control architecture, path planning, motion control.
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