This paper addresses the problem of selecting route to a given destination on a load map under a dynamic environment. The proposed solution is using a genetic algorithm adopting viral infection. The method is to use viruses as domain specific knowledge. A part of an arterial road is regarded as a virus. We generate a population of viruses in addition to a population of routes. Crossover and infection determine the optimal combination of viruses. When trafsic congestion changes during driving, an alternative route can be generated using viruses and other routes in the population in the shortest time. Experiments using actual road maps show the infection is effective for the problem.
This paper provides a control algorithm for terrain following of the self-contained semi-fixed gait hexapod walking machine "MELCRAB-2." MELCRAB-2 uses decoupled freedoms of the leg mechanism for the bodypropelling motion and the terrain-adapting motion. The mechanism simplifies the drive and control of the walking machine over rough terrain. The geometry of the leg mechanism is described, and its inverse kinematics is solved analytically. An algorithm for following the terrain and' adjusting the body altitude is introduced. # -309 -
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.