: : The Development of a Fully Autonomous Ground Vehicle (FAGV)

As a first step toward the creation of a fully autonomous vehicle that operates in a real world environment, we are currently developing a prototype Autonomous Ground Vehicle (AGV) for use in factories and other industrial/business sites based on behavior-based Artificial Intelligence (AI) control. This flexible and Fully Autonomous Ground Vehicle (FAGV) is expected to operate efficiently in a normal industrial environment without any external guidance. The crucial technique employed is a non-Cartesian way of organizing software agents for the creation of a highly responsive control program. The resulting software is considerably reduced in size (up to one thousandth the size of conventional control programs for similar applications). Through numerous experiments using mobile robots we confirmed that these new control programs excel in functionality, efficiency, flexibility and robustness. The second key technique in the planning stage is evolutionary computation, of which Genetic Algorithms are a principal technique. An online, realtime evolution of the control program such as the one demonstrated recently by Floreano and Mondada (1994) will be incorporated in later phases of the project to make FAGVs adaptable to any given operational environment (e.g., to a specific factory floor with its own idiosyncrasies) after deployment.

The first prototype FAGV has an active vision and behavior-based control system. The vision process itself is also behavior-based. It allows extremely efficient processing of navigation-related visual signals in a manner not unlike that in small animals and directly generates control signals to on-board actuators (motors and steering mechanisms). Other sensor inputs such as infra red (IR) and tactile sensor inputs are also used to maneuver the FAGV in close proximity to obstacles, habitat boundaries, and other moving objects (e.g., humans, mobile robots, other AGVs).

The control structure of the vehicle and experiments which demonstrate the ability of prototype FAGV to fully autonomously maneuver itself in a habitat using the above techniques are described.

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