COPING WITH LIMITED ON-BOARD MEMORY AND COMMUNICATION BANDWIDTH IN MOBILE-ROBOT SYSTEMS

Much effort has gone into studying navigation algorithms for mobile-robot systems. However, although mobile-robot systems often suffer from a lack of adequate on-board memory and communication bandwidth, little work has been done on techniques to solve these problems. Two algorithm-implementation strategies are examined to solve the memory-limitation and communication-bandwidth-limitation problems associated with the navigation of single or multiple robots in large dynamic environments. On-board main-memory-management mechanisms, cache policies, auxiliary-memory data structures, and two path planners are explored by simulations based on a new navigation algorithm. One- and two-level caches with one- and two-level planning, respectively, are investigated; these can easily be extended to schemes with more levels. Our results show that among the seven (three local and four global) cache policies studied, the predicted-window, aisle, and via-point policies overcame the above limitations without compromising robot performance. Therefore, one or more of these three policies can be used with implementation strategies to deal with the memory-limitation and communication-bandwidth-limitation problems encountered in real-world mobile-robot navigation. Our results can also be very useful in the domain of Intelligent Vehicle Highway Systems (IVHS), where the main memory of the on-board computer may be too small to hold all of the road network and other useful information.