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Towards a theory of sensory robotics

Published online by Cambridge University Press:  09 March 2009

Jan Pinkava
Affiliation:
A.I. & Robotics Research Group, Department of Computer Science, The University College of Wales, Aberystwyth, SY23 3BZ (UK)

Summary

A partial review of some efforts in robotics research is presented. We identify two broad categories of work: one characterised by application-driven experimental engineering, the other by a more ‘scientific’ approach based on testing theoretical models through implementation. We argue that although the former represents some of the best practical results obtained to-date, this experiment-first-theory-later approach does not contribute to a homogeneous body of knowledge. If robotics is to make measured progress, sound theoretical ground is needed. We argue for a task-specific paradigm for future theoretical work founded on formal models. To this end, we present a general analysis of a sensory robotic system, and identify key elements that must be defined in any formal model before we can decide what sensory information is useful for a given task.

Type
Article
Copyright
Copyright © Cambridge University Press 1990

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References

1.Brady, M., “Artificial Intelligence and RoboticsArtificial Intelligence 26, 79121 (1985).CrossRefGoogle Scholar
2.de Saint Vincent, A.R.A 3-D perception system for the mobile robot HILAREIEEE Int. Conf. on Robotics and Automation,San Francisco, (04, 1986). p. 1105.Google Scholar
3.Hughes, A.D. “Image understanding in surveillance systems”. In: IEE Electronics Division Colloquium Digest 1987/49. IEEE (04, 1987).Google Scholar
4.Raibert, M.H., Brown, H.B. Jr. and Murthy, S.S., “3-D balance using 2-D algorithms” In: (Brady, M. and Paul, R., editors) Proceedings International Symposium on Robotics Research (MIT press, Cambridge, Mass., 1984).Google Scholar
5.Lee, M.H., “The three robot worlds–a view point (a review of the different goals of robotics research)Robotica 2, 7174 (01, 1984).CrossRefGoogle Scholar
6.Taylor, P.M., Taylor, G.E. and Gibson, I., “A multisensory approach to shoe assembly” In: (M. Briot, editor) Proceedings 6th RoViSeC, (1986) pp. 117126.Google Scholar
7.Bajcsy, R., “Active Perception vs Passive Perception” Technical report (Dept. CIS, University of Pennsylvania, 12, 1985).Google Scholar
8.Allen, P.K., “Sensing and Describing 3-D StructureIn: IEEE Conf. on Robotics and Automation (04, 1986) pp. 126131.Google Scholar
9.Allen, P. and Bajcsy, R., “Two Sensors are Better than One: Example of Integration of Vision and Touch” Technical report (Dept. CIS, University of Pennsylvania, 09, 1985).Google Scholar
10.Allen, P.K., “Integrating Vision and Touch for Object Recognition Tasks.” Int. J. of Robotics Research 1(6) (12, 1988).Google Scholar
11.Beni, G., Hackwood, S., Hornak, L.A. and Jackel, J.L., “Dynamic Sensing for Robots: An Analysis and ImplementationInt. J. of Robotics Research, 2(2) 5161 (Summer, 1983).CrossRefGoogle Scholar
12.Durrani-Whyte, H.F., “Integration, Coordination and Control of multi-sensor Robot Systems” PhD thesis (Dept. CIS, University of Pennsylvania, 1986).Google Scholar
13.Hager, G., “Active reduction of uncertainty in multi-sensor systems” Technical report (Dept. CIS, University of Pennsylvania, 09, 1986).Google Scholar
14.Hillis, D.W., “Active touch sensing” Technical report (Massachusetts Institute of Technology, 04, 1981).Google Scholar
15.Lee, I. and Goldwasser, S.M., “A distributed testbed for active sensory processing” Technical report (Dept. CIS, University of Pennsylvania, 03, 1985).Google Scholar
16.Sansfield, S.A., “A rudimentary active, multimodal, intelligent system for object categorization” Technical report (Dept. CIS, University of Pennsylvania, 11, 1985).Google Scholar
17.Mowforth, P. and Bratko, I.AI and Robotics; Flexibility and IntegrationRobotica 5, 9398 (1987).CrossRefGoogle Scholar
18.Lee, M.H., Intelligent Robotics (Open University Press, Milton Keynes, 1989).CrossRefGoogle Scholar
19.Clocksin, W.F., Bromley, J.S.E., Davey, P.G., Vidler, A.R. and Morgan, C.G.An Implementation of Model-Based Visual Feedback for Robot Arc Welding of Thin Sheet SteelInt. J. of Robotics Research 4(1), 1326 (Spring, 1985).CrossRefGoogle Scholar
20.Trevelyan, J.P., Kovesi, P.D. and Ong, M.C. “Motion control for a sheep shearing robot” In: (Brady, M. and Paul, R., editors) proceedings International Symposium on Robotics Research (MIT press, Cambridge, Mass., 1984).Google Scholar
21.Aleksander, I., Thomas, W.V. and Bowden, P.A.Wisard: A radical step forward in image recognition”. Sensor Review (07, 1984).CrossRefGoogle Scholar
22.Albus, J.S.Brains, Behaviour, and Robotics (BYTE publications New York, 1981).Google Scholar
23.Kent, E.W. and Albus, J.S., “Servoed world models as interfaces between robot control systems and sensory dataRobotica 2, 1725 (1984).CrossRefGoogle Scholar
24.Andrew, A.M.How Robotics Expands AIRobotica 5, 111115 (1987).CrossRefGoogle Scholar
25.Arbib, M.A., Foury, A.J. and Moll, R.N., A Basis for Theoretical Computer Science (Springer-Verlag, Berlin 1981).CrossRefGoogle Scholar
26.Richardson, J.M. and Marsh, K.A.Fusion of multisensor data Int. J. of Robotics Research 7(6) 7896 (1988).CrossRefGoogle Scholar
27.Hager, G.D., Active Reduction of Uncertainty in Multi-Sensor Systems. PhD thesis (Dept. CIS, University of Pennsylvania, 1988).Google Scholar
28.Grimson, W.E.L., “Disambiguating sensory interpretations using minimal sets of sensory data” Technical report (Artificial Intelligence Lab, Massachusetts Institute of Technology, 1986).Google Scholar
29.Porrill, J., “Optimal combination of constraints for geometrical sensor data Int. J. of Robotics Research 7(6) 6677 (12, 1988).CrossRefGoogle Scholar
30.Garvey, T.D., Lowrance, J.D. and Fischler, M.A., “An inference technique for integrating knowledge from disparate sources” 7th IJCAI 319–25Google Scholar
31.Stansfield, S.A., “A robotic perceptual system utilizing passive vision and active touchInt. J. of Robotics Research, 7(6) 138160 (12, 1988).CrossRefGoogle Scholar
32.Henderson, T. and Shilcrat, E., “Logical sensor systemsJ. Robotic Systems, 1(2) 169193 (1984).CrossRefGoogle Scholar
33.Brooks, R.A., “Symbolic error analysis and robot planningInt. J. of Robotic Research 1(4) 2968 (Winter, 1982).CrossRefGoogle Scholar
34.Durrant-Whyte, H.F., “Consistent integration and propagation of disparate sensor observations.” Technical report (Dept. CIS, University of Pennsylvania, 01, 1986).Google Scholar
35.Milovanovic, R.Towards sensor-based general purpose robot programming languageRobotica 5, 309316 (1012 1987).CrossRefGoogle Scholar
36.Rock, S.T., “Intelligent Robot Programming: you can't get there from here – a viewpointRobotica 6, 333338 (1988).CrossRefGoogle Scholar
37.Lozano-Pérez, T., “Robot ProgrammingProceedings of the IEEE, 71(7) 821841 (07, 1983).CrossRefGoogle Scholar
38.Yin, B., “Using Vision Data in an Object-Level Robot Language-RAPT”. Int. J. of Robotics Research, 6(1) 4358 (Spring, 1987).CrossRefGoogle Scholar
39.Nitzen, D. “Assessment of robotic sensors”. Technical report (SRI International, Menlo Park, California, 04, 1980).Google Scholar
40.Hall, D.J., “Robotic sensing devices.” Technical report (Carnegie-Mellon University, 03, 1984).Google Scholar
41.Nicholls, H.R., “A review of tactile sensing technology” Technical report (Robotics Research Group, Aberystwyth, 04, 1984).Google Scholar
42.Davey, P.G., “Sensors for Robots: Turning Potential into Profits,” In: Int Symp and Exposition on Robots (19th ISIR), Sydney, Australia (11, 1988).Google Scholar
43. Sensors and actuators (Pub. Elsevier Sequoia, S.A.)Google Scholar
44. Sensor review (IFS Publishers, Bedford).Google Scholar
45.Chambers, C., “Rule-driven adaptive signal processing” In: IEE Electronics Division Colloquium Digest 1987/49, IEE (04, 1987).Google Scholar
46.Mason, P. and Buggy, T.W., “Knowledge-based interpretation of passive sonar data” In: IEE Electronics Division Colloquium Digest 1987/49. IEE (04, 1987).Google Scholar
47.Mitiche, A. and Aggarwal, J.K., Multiple sensor integration/fusion through image processing: a review. “Opt. Eng (USA) 25(3) 380–6 (03, 1986).Google Scholar
48.Pinkava, J., “Formal modelling of perception in robots”. Technical Report (UCW-RRG-TR-133–88, UCW Aberystwyth, 07, 1988).Google Scholar
49.Grupen, R.A., Henderson, T.C. and McCammon, I.D., “A Survey of General-Purpose ManipulationInt. J. of Robotics Research 8(1) 3862 (02, 1989).CrossRefGoogle Scholar
50.de Groot, A.W.. “Effect of sensor size in robotic tactile sensor arrays. “Robotica 6, 285287 (10, 1988).CrossRefGoogle Scholar
51.Malcolm, C.A. and Fothergill, A.P., “Some architectural implications of the use of sensors” Technical report (Univ. Edinburgh, 09 1986), presented at Pisa NATO conference on Robotics.Google Scholar
52.Smithers, T. and Malcolm, C. “A behavioural approach to robot task planning and off-line programming” Technical report (Univ. Edinburgh, 1987).Google Scholar
53.Dixon, J.R.On research methodology towards a scientific theory of engineering designAI EDAM 1(3) 145157 (1987).Google Scholar
54.Lozano-Pérez, T., “Spatial Planning: A Configuration Space ApproachIEEE Transactions on Computers, C-32(2) (02, 1983).CrossRefGoogle Scholar
55.Brooks, R.A., “Planning collision free motions for pick and place operations” Technical Report (AIM-725, MIT, 05, 1983).Google Scholar
56.Donald, B.R., “Motion planning for six degrees of freedom” Technical Report (AI lab 791, MIT, 05, 1984).CrossRefGoogle Scholar
57.Graf, D.H. and Lalonde, W.R., “NARM: A neural controller for collision-free movement of general robot manipulators.” Proceedings of IEEE ICNN'88 1, 19 (1988).Google Scholar
58.Nguyen, V., “Constructing stable graspsInt. J. of Robotics Research 8(1) 2637 (02, 1989).CrossRefGoogle Scholar
59.Lozano-Pérez, T., Mason, M.T. and Taylor, R.H., “Automatic Synthesis of Fine-Motion Strategies for RobotsInt. J. of Robotics Research 3(1) 224 (1984).CrossRefGoogle Scholar
60.Erdmann, M. and Mason, M.T.An Exploration of Sensorless ManipulationIn: IEEE Int. Conf. on Robotics and Automation IEEE (04, 1986). pp. 15691574.Google Scholar
61.Erdmann, M.A., “On Motion Planning with Uncertainty”. Master's thesis (MIT AI Lab, 1984).Google Scholar
62.Smithers, T. and Malcolm, C., “Programming robotic assembly in terms of task achieving behavioural modules.” Technical Report (EDAI 417, Dept. AI, Univ. Edinburgh, 1988).Google Scholar