BIOLOGICALLY BASED ARTIFICIAL NAVIGATION SYSTEMS: REVIEW AND PROSPECTS
Abstract
Diverse theories of animal navigation aim at explaining how to determine and maintain a course from one place to another in the environment, although each presents a particular perspective with its own terminologies. These vocabularies sometimes overlap, but unfortunately with different meanings. This paper attempts to define precisely the existing concepts and terminologies, so as to describe comprehensively the different theories and models within the same unifying framework. We present navigation strategies within a four-level hierarchical framework based upon levels of complexity of required processing (Guidance, Place recognition-triggered Response, Topological navigation, Metric navigation). This classification is based upon what information is perceived, represented and processed. It contrasts with common distinctions based upon the availability of certain sensors or cues and rather stresses the information structure and content of central processors. We then review computational models of animal navigation, i.e. of animats. These are introduced along with the underlying conceptual basis in biological data drawn from behavioral and physiological experiments, with emphasis on theories of "spatial cognitive maps". The goal is to aid in deriving algorithms based upon insights into these processes, algorithms that can be useful both for psychobiologists and roboticists. The main observation is, however, that despite the fact that all reviewed models claim to have biological inspiration and that some of them explicitly use "Cognitive Map"-like mechanisms, they correspond to different 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.
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Some teleost spatial strategies necessarily involve complex learning and memory capabilities and require flexible representational mechanisms, the most remarkable of which is allocentric navigation based on map-like spatial memory.
“Some of these spatial strategies necessarily involve complex learning and memory capabilities and require the concurrence of flexible representational mechanisms, the most remarkable of which probably is allocentric navigation based on map-like spatial memory”
From Spatial Cognition in Teleost Fish: Strategies and Mechanisms (2021) · cites this paper as [51]
Shortcutting and detouring behavior has been proposed as key evidence to distinguish allocentric navigation based on cognitive maps or survey representations from more simple navigational strategies.
“shortcutting and detouring behavior has been proposed as a key evidence to distinguish allocentric navigation based on cognitive maps or survey representations from more simple navigational strategies”
From Spatial Cognition in Teleost Fish: Strategies and Mechanisms (2021) · cites this paper as [51]
A number of neurobiologically inspired, fully mechanistic computational models of navigational behavior have been developed to account for the ability of animals relying on allocentric frameworks to perform path planning without resorting to mentalistic explanations.
“A number of neurobiologically inspired, fully mechanistic computational models of navigational behavior have been developed to account for the ability of animals relying on allocentric frameworks to perform path planning, without the need to resort to “mentalistic” explanations”
From Spatial Cognition in Teleost Fish: Strategies and Mechanisms (2021) · cites this paper as [51]
Such hypothetical memory representations presumably encode the spatial relationships between all known places and landmarks in a common allocentric reference frame or unitary global map, accessible as a whole, and can operate to infer spatial relationships between any represented elements.
“Such hypothetical memory representations presumably encode the spatial relationships between all the known places and landmarks in a common allocentric reference frame or unitary global map, accessible as a whole, and that can operate to infer the spatial relationships between any of the represented elements.”
From Spatial Cognition in Teleost Fish: Strategies and Mechanisms (2021) · cites this paper as [51]
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References 160 · Cited by 363
- Authors
- TRULLIER, O., WIENER, S. I., BERTHOZ, A., & MEYER, J.-A.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- École Normale Supérieure - PSL (FR)
- Corresponding author
- TRULLIER, OLIVIER
- ORCID
- WIENER, SIDNEY I.
- Venue
- Progress in Neurobiology
- Publisher
- Elsevier BV
- Published
- 1997-04
- Volume
- 51
- Issue
- 5
- Pages
- 483-544
- ISSN
- 0301-0082 (ISSN-L)
- OpenAlex
- W2041559710
- Cited by
- 363
- References
- 160
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 11 · 2023: 7 · 2022: 4 · 2021: 12 · 2020: 6 · 2019: 9 · 2018: 12 · 2017: 15 · 2016: 14 · 2015: 9 · 2014: 11 · 2013: 13 · 2012: 23
- FWCI
- 41.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Progress in Neurobiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Spatial Cognition and Navigation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Keywords
- animal navigation, cognitive maps, animats, topological navigation, place recognition, guidance, bio-inspired robotics
- MeSH terms
- Animals, Electrophysiology, Locomotion, Models, Biological, Mental Recall, Space Perception
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