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A Perspective on Cognitive Robot Research and Development

Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee 37235, USA

E-mail Address: kaz.kawamura@vanderbilt.edu

https://doi.org/10.1142/S0219843623500238Cited by:1 (Source: Crossref)

This article is part of the issue:

Special Issue in Celebrating 20th Anniversary
Guest Editors: Ming Xie, John Weng and Giulio Sandini

Abstract

The purpose of this paper is to present my personal journey in the last 30-plus years of research and development efforts on a cognitive robotic system called Intelligent Soft Arm Control (ISAC). In doing so, I will highlight how our team approached solving certain robot intelligence, communication, and control problems.

Keywords:

References

1. A. D. Baddeley and G. Hitch, Working Memory, in The Psychology of Learning and Motivation: Advances in Research and Theory, ed. G. A. Bower (Academic Press, New York, 1974), pp. 47–89. Google Scholar
2. A. D. Baddeley, Working Memory (Clarendon Press, Oxford, 1986). Google Scholar
3. T. S. Braver and D. M. Barch, A theory of cognitive control, aging cognition, and neuromodulation, Neurosci. Behav. Rev. 26 (2002) 809–817. Crossref, Web of Science, Google Scholar
4. A. Cangelosi and M. Schlsign, Developmental Robotics: From Babies to Robots (MIT Press, 2015). Crossref, Google Scholar
5. Discover Magazine, Discover Roundtable, The Future of Humanoids Robots (2000), pp. 84–90. Google Scholar
6. J. A. Driscoll et al., A visual attention network for a humanoid robot, in Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (IEEE, 1998), pp. 1968–1974. Crossref, Google Scholar
7. K. Kawamura and T. E. Davis (eds.), Robotics and autonomous systems, in Int. Workshop Biorobotics: Human-Robot Symbiosis (Elsevier, 1996), pp. 1–291. Google Scholar
8. G. M. Edelman and G. Tononi, A Universe of Consciousness: How Matter Becomes Imagination (Basic Books, 2000). Google Scholar
9. E. Erdemir et al., Towards a cognitive robot that uses internal rehearsal to learn affordance relations, in Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IEEE, 2008), pp. 2016–2021. Crossref, Google Scholar
10. T. J. Hwu and J. L. Krichmar, Nuerorobotics: Neuroscience and Robots (MIT Press, 2022). Google Scholar
11. IEEE Computer Society, Humanoid robotics, IEEE Intell. Syst. Appl. 15 (2000) 12–77. Web of Science, Google Scholar
12. IEEE Spectrum, For Better or Worse, Tesla Bot is Exactly We Expected (2022), https://spectrum.ieee.org/tesla-optimus-robot. Google Scholar
13. S. Kajita et al., Introduction to Humanoid Robotics, Springer Tracts in Advanced Robotics, Vol. 101 (Springer-Verlag, 2014). Crossref, Google Scholar
14. K. Kawamura et al., Intelligent robotic systems in service of the disabled, IEEE Trans. Rehabil. Eng. 3 (1995) 14–21. Crossref, Google Scholar
15. K. Kawamura, R. T. Pack and M. Iskarous, Design philosophy for service robots, Robot. Auton. Syst. 18 (1996) 109–116. Crossref, Web of Science, Google Scholar
16. K. Kawamura et al., ISAC: Foundations in human-humanoid interaction, IEEE Intell. Syst. Appl. 15 (2000) 38–45. Crossref, Web of Science, Google Scholar
17. K. Kawamura et al., A parallel distributed cognitive control system for a humanoid robot, Int. J. Humanoid Rob. 1(1) (2004) 65–93. Link, Google Scholar
18. K. Kawamura et al., Implementation of cognitive control for a humanoid robot, Int. J. Humanoid Rob. 5(4) (2008) 547–586. Link, Web of Science, Google Scholar
19. K. Kawamura and W. Browne, Cognitive robotics, in Encyclopedia of Complexity and Systems Science, ed. R. A. Myers (Springer, 2009), pp. 1109–1126. Crossref, Google Scholar
20. I. Kotseruba and J. K. Tsotsos, 40 years of cognitive architectures: Core cognitive abilities and practical applications, Artif. Intell. Rev. 53 (2020) 17–94. Crossref, Web of Science, Google Scholar
21. M. Iskarous, R. T. Pack and K. Kawamura, A parallel fuzzy controller for a manipulator with flexible joints, in Proc. First Asian Control Conf. (Tokyo Metropolitan Institute of Technology, Tokyo, 1994), pp. 619–622. Google Scholar
22. R. T. Pack et al., Intelligent machine architecture for object-based system integration, in Proc. Int. Conf. Advanced Intelligent Mechatronics (IEEE, 1997), p. 151. Crossref, Google Scholar
23. R. A. Peters et al., The sensory egosphere as a short-term memory for humanoid, in Proc. 2nd IEEE-RAS Int. Conf. Humanoid Robots (IEEE, 2001), pp. 451–459. Google Scholar
24. G. Sandini, private communication (2023). Google Scholar
25. G. Schillaci, V. V. Hafner and B. Lara, Exploration behaviors, body representations, and simulation processes for the development of cognition in artificial agents, Front. Rob. AL 3 (2016) 1–18. Google Scholar
26. TCCR (Technical Committee for Cognitive Robotics) (2014), https://www.ieee-ras.org/cognitive-robotics. Google Scholar
27. D. Vernon, 10: Cognitive Architectures, in Cognitive Robotics, eds. A. Cangelosi and M. Asada (MIT Press, 2022). Crossref, Google Scholar
28. T. S. Braver and J. D. Cohen, On the control of control: The role of dopamine in regulating prefrontal function and working memory, in Control of Cognitive processes: Attention and Performance XVIII (MIT Press, 2000), pp. 713–736. Google Scholar
29. J. L. Phillips and D. C. Noelle, A biologically inspired working memory framework for robots, in IEEE International Workshop on Robots and Human Interactive Communication (2005), 599–604. Crossref, Google Scholar