Abstract-This paper describes how decentralized control theory can be used to analyze the control of multiple cooperative robotic vehicles. Models of cooperation are discussed and related to the input/output reachability, structural observability, and controllability of the entire system. Whereas decentralized control research in the past has concentrated on using decentralized controllers to partition complex physically interconnected systems, this work uses decentralized methods to connect otherwise independent nontouching robotic vehicles so that they behave in a stable, coordinated fashion. A vector Liapunov method is used to prove stability of two examples: the controlled motion of multiple vehicles along a line and the controlled motion of multiple vehicles in formation. Also presented are three applications of this theory: controlling a formation, guarding a perimeter, and surrounding a facility.

Absstract-This paper presents a vision module which is able toguide an eye-in-hand robot through general servoing and tracking problems using off-the-shelf image processing equipment. The vision module uses the location of binary image features from a camera on the robot's endeffector to control the position and one degree of orientation of the robot manipulator. A unique feature-based trajectory generator provides smooth motion between the actual image features and the desired image features even with asynchronous and discontinuous vision updates. By performing the trajectory generation in image feature space, image processing constraints such as the feature extraction time may be accounted for when determining the appropriate segmentation and acceleration times of the trajectory. Experimental results of a PUMA robot tracking objects with vision feedback are discussed.

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