BIOLOGICALLY-BASED ARTIFICIAL NAVIGATION SYSTEMS - REVIEW AND PROSPECTS

Diverse theories of animal navigation aim at explaining how to determi ne and maintain a course from one place to another in the environment, although each presents a particular perspective with its own terminol ogies. These vocabularies sometimes overlap, but unfortunately with di fferent meanings. This paper attempts to define precisely the existing concepts and terminologies, so as to describe comprehensively the dif ferent theories and models within the same unifying framework. We pres ent navigation strategies within a four-level hierarchical framework b ased upon levels of complexity of required processing (Guidance, Place recognition-triggered Response, Topological navigation, Metric naviga tion). This classification is based upon what information is perceived , represented and processed. It contrasts with common distinctions bas ed upon the availability of certain sensors or cues and rather stresse s the information structure and content of central processors. We then review computational models of animal navigation, i.e. of animals. Th ese are introduced along with the underlying conceptual basis in biolo gical data drawn from behavioral and physiological experiments, with e mphasis on theories of ''spatial cognitive maps''. The goal is to aid in deriving algorithms based upon insights into these processes, algor ithms that can be useful both for psychobiologists and roboticists. Th e main observation is, however, that despite the fact that all reviewe d models claim to have biological inspiration and that some of them ex plicitly use ''Cognitive Map''-like mechanisms, they correspond to dif ferent levels of our proposed hierarchy and that none of them exhibits the main capabilities of real ''Cognitive Maps'' - in Tolman's sense - that is, a robust capacity for detour and shortcut behaviors. (C) 19 97 Elsevier Science Ltd.