Autonomous search by robots and animals: A survey

This paper is a survey of research on autonomous search strategies which originate in engineering and biology. Our motivation is to identify methods of search in an essentially two-dimensional Euclidean space, which can be applied to the area of demining. Such search strategies are based on spatio-temporal distributions. These distributions may be known in advance, because of prior intelligence or through the use of remote sensing, or they may be the result of on-line gathering of information as the search progresses, or of both. We first review the literature on search and coordination which emanates from the field of robotics, we then summarize significant research in the field of animal search, and also discuss relevant results in robotics which are inspired by animal behavior.

[1]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[2]  Toshio Fukuda,et al.  Self-organization of cellular robots using random walk with simple rules , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[3]  François G. Pin,et al.  Autonomous mobile robot navigation and learning , 1989, Computer.

[4]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[5]  J. Gibbon,et al.  Tracking a fluctuating environment: a study of sampling , 1988, Animal Behaviour.

[6]  Jean-Claude Latombe,et al.  A Monte-Carlo algorithm for path planning with many degrees of freedom , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[7]  R. D. Harkness,et al.  Central place foraging by an ant (Cataglyphis bicolor Fab.): a model of searching , 1985, Animal Behaviour.

[8]  D. Koditschek,et al.  The construction of analytic diffeomorphisms for exact robot navigation on star worlds , 1991 .

[9]  Erol Gelenbe,et al.  Stability of the Random Neural Network Model , 1990, Neural Computation.

[10]  Barbara Hayes-Roth,et al.  Intelligent Control , 1994, Artif. Intell..

[11]  P. Chesson,et al.  Sunfish foraging among patches: the patch-departure decision , 1989, Animal Behaviour.

[12]  Ming C. Lin,et al.  An opportunistic global path planner , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[13]  B. Faverjon,et al.  A practical approach to motion-planning for manipulators with many degrees of freedom , 1991 .

[14]  G. Beni,et al.  Stationary waves in cyclic swarms , 1992, Proceedings of the 1992 IEEE International Symposium on Intelligent Control.

[15]  M. Noda,et al.  Local prey search based on spatial memory and expectation in the planktivorous reef fish, Chromis chrysurus (Pomacentridae) , 1994, Animal Behaviour.

[16]  Nestor A. Schmajuk,et al.  Place Learning and the Dynamics of Spatial Navigation: A Neural Network Approach , 1993, Adapt. Behav..

[17]  Erol Gelenbe,et al.  Global behavior of homogeneous random neural systems , 1991 .

[18]  Dario Maio,et al.  Map Learning and Clustering in Autonomous Systems , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Maja J. Mataric.  Distributed approaches to behavior control , 1992, Other Conferences.

[20]  Moshe Tennenholtz,et al.  On the Synthesis of Useful Social Laws for Artificial Agent Societies (Preliminary Report) , 1992, AAAI.

[21]  Jean-Louis Deneubourg,et al.  Harvesting by a group of robots , 1992 .

[22]  Lynne E. Parker.  Designing control laws for cooperative agent teams , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[23]  Philip F. Spelt,et al.  Development and training of a learning expert system in an autonomous mobile robot via simulation , 1989, Simul..

[24]  Deanne F. Johnson,et al.  Patch choice and meal size of foraging rats as a function of the profitability of food , 1989, Animal Behaviour.

[25]  Jing Wang,et al.  Theoretical problems for the realization of distributed robotic systems , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[26]  Simon Benhamou,et al.  Spatial memory and searching efficiency , 1994, Animal Behaviour.

[27]  Roger M. Evans,et al.  Foraging strategies of American white pelicans , 1992 .

[28]  Jean-Claude Latombe,et al.  Robot Motion Planning: A Distributed Representation Approach , 1991, Int. J. Robotics Res..

[29]  Daniel E. Koditschek,et al.  Exact robot navigation by means of potential functions: Some topological considerations , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[30]  Erol Gelenbe,et al.  Random Neural Networks with Negative and Positive Signals and Product Form Solution , 1989, Neural Computation.

[31]  Simon Benhamou,et al.  Orientation and foraging movements in a patchy environment by the ant Serrastruma lujae (formicidae-myrmicinae) , 1993, Behavioural Processes.

[32]  A. Houston,et al.  Interference and the ideal free distribution , 1995, Animal Behaviour.

[33]  Erol Gelenbe,et al.  Autonomous search for mines , 1998, Eur. J. Oper. Res..

[34]  John R. Koza,et al.  Evolution of Food-Foraging Strategies for the Caribbean Anolis Lizard Using Genetic Programming , 1992, Adapt. Behav..

[35]  Nageswara S. V. Rao.  Algorithmic framework for learned robot navigation in unknown terrains , 1989, Computer.

[36]  H T Blair,et al.  Maps, routes, and the hippocampus: A neural network approach , 1993, Hippocampus.

[37]  J. Brian Burns,et al.  Path planning using Laplace's equation , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[38]  Ichiro Suzuki,et al.  Distributed motion coordination of multiple mobile robots , 1990, Proceedings. 5th IEEE International Symposium on Intelligent Control 1990.

[39]  P. Schönemann.  On artificial intelligence , 1985, Behavioral and Brain Sciences.

[40]  Jean-Claude Latombe,et al.  Robot motion planning , 1970, The Kluwer international series in engineering and computer science.

[41]  D. W. Stephens,et al.  How constant is the constant of risk-aversion? , 1986, Animal Behaviour.

[42]  Alessandro Saffiotti.  Autonomous robot navigation , 1998 .

[43]  Simon Benhamou,et al.  Optimal sinuosity in central place foraging movements , 1991, Animal Behaviour.

[44]  Alan C. Kamil,et al.  The detection of cryptic prey by blue jays (Cyanocitta cristata) I: the effects of travel time , 1985, Animal Behaviour.

[45]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[46]  Marcelo H. Cassini.  Searching strategies within food patches in the armadillo Chaetophractus vellerosus , 1993, Animal Behaviour.

[47]  Zvi Shiller,et al.  Dynamic motion planning of autonomous vehicles , 1991, IEEE Trans. Robotics Autom..

[48]  Erol Gelenbe,et al.  Learning in the Recurrent Random Neural Network , 1992, Neural Computation.

[49]  Roberta Lynn Soltz.  Foraging Path Selection in Bumblebees: Hindsight or Foresight? , 1986 .

[50]  John McNamara,et al.  A simple model of information use in the exploitation of patchily distributed food , 1985, Animal Behaviour.

[51]  Charles W. Warren,et al.  Global path planning using artificial potential fields , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[52]  Hongyan Wang,et al.  Social potential fields: A distributed behavioral control for autonomous robots , 1995, Robotics Auton. Syst..

[53]  Edwin S. H. Hou,et al.  Mobile robot path planning based on hierarchical hexagonal decomposition and artificial potential fields , 1994, J. Field Robotics.