In previous work, we demonstrated the feasibility of perceptual navigation algorithms used to intercept fly balls. In this paper we expand the optical acceleration cancellation heuristic to also intercept ground balls. We used computer simulations and experiments with mobile robots with various bail trajectories and different initial positions of the fielder to test our new model. A new robotic system with improved vision and faster processing was developed for experimentally intercepting ground balls. The results support the generality of viewer based interception heuristics for both fly balls and ground balls.

Human based algorithms; to catch fly balls have been research and studied. In the paper, the validity of the human models are tested by catching balls that are dropped vertically downward. The regular OAC (optical acceleration cancellation) and the inverted OAC models are simulated first, and then tested experimentally with a mobile robot. The simulation and the experimental results show that both methods are able to intercept the dropped ball, but the initial and final motions are different. A digital image processing program, DVRobot, was written to process digital images very quickly.

Human based vision algorithms for interception of flying balls in one-dimension have been researched and studied. We develop new perceptual strategies for three-dimensional space that are robust and simple. Results from simulations show the feasibility of human vision algorithms for ball catching. This paper discusses the experimental validation of two perceptual algorithms: linear optical trajectory and the optical acceleration cancellation.