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.