로봇학회논문지 (The Journal of Korea Robotics Society)

  • 제7권3호
  • /
  • Pages.182-193
  • /
  • 2012
  • /
  • 1975-6291(pISSN)
  • /
  • 2287-3961(eISSN)
한국로봇학회 (Korea Robotics Society)
권호 표지
DOI QR코드

DOI QR Code

로봇의 어포던스 지각 과정 및 계층 분석법을 이용한 우선 순위 동작 결정

Affordance Perception And Behavior Planning Based on Analytic Hierarchy Process

  • Lee, Geun-Ho (School of Information Science, JAIST (Japan Advanced Institute of Science and Technology)) ;
  • Kwon, Chul-Min (School of Information Science, JAIST (Japan Advanced Institute of Science and Technology)) ;
  • Ikeda, Akihiro (School of Information Science, JAIST (Japan Advanced Institute of Science and Technology)) ;
  • Chong, Nak-Young (School of Information Science, JAIST (Japan Advanced Institute of Science and Technology))
  • 투고 : 2012.04.23
  • 심사 : 2012.07.04
  • 발행 : 2012.08.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper presents a new behavior planning scheme for autonomous robots, allowing them to handle various objects used in our daily lives. The key idea underlying the proposed scheme is to use affordance concepts that provide a robot with action possibilities triggered by a relation between the robot and objects around it. Specifically, the robot attempts to find the affordances and to determine the most adequate action among them. Through a series of the perception processes, robot motions can be planned and performed to complete assigned tasks. What is of particular importance from the practical point of view is a decision making capability to determine the best choice by comparing the human's body characteristics and behavioral patterns as criteria with action possibilities as alternatives. For this, the analytic hierarchy process (AHP) technique is employed to systematically evaluate the correlation between the criteria and the alternatives. Moreover, the alternatives arranged in order of priority through the decision making process enable the robot to have redundant solutions for the assigned task, resulting in flexible motion generation. The effectiveness and validity of the proposed scheme are verified by performing extensive simulations using objects of our daily use.

키워드

참고문헌

  1. A. Miller, S. Knoop, H. Christensen, and P. Allen, "Automatic grasp planning using shape primitives", Proc. IEEE Int. Conf. Robotics and Automation, pp.1824-1829, 2003
  2. M. Moussa, "Combining expert neural networks using reinforcement feedback for learning primitive grasping behavior", IEEE Trans. Neural Networks, vol.15, no.3, pp.629-638, 2004 https://doi.org/10.1109/TNN.2004.824412
  3. J. Aleotti and S. Caselli, "Grasp recognition in virtual reality for robot pregrasp planning by demonstration", Proc. IEEE Int. Conf. Robotics and Automation, pp.2801-2806, 2006
  4. M. Tenorth, U. Klank, D. Pangercic, and M. Beetz, "Web-enabled robots: robots that use the web as an information", IEEE Robotics and Automation Magazine, vol.18, no.2, pp.58-68, 2011 https://doi.org/10.1109/MRA.2011.940993
  5. E. Pacchierotti, H. Christensen, and P. Jensfelt, "Design of an office-guide robot for social interaction studies", Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp.4965-4970, 2006
  6. C.C. Kemp, A. Edsinger, and E. Torres-Jara, "Challenges for robot manipulation in human environments", IEEE Robotics and Automation Magazine, vol.14, no.1, pp.20-29, 2007 https://doi.org/10.1109/MRA.2007.339604
  7. A. Wykowska, A. Maldonado, M. Beetz, and A. Schubo, "How humans optimize their interaction with the environment: the impact of action context on human perception", Communications in Computer and Information Science, vol.44, no.2, pp.162-172, 2009 https://doi.org/10.1007/978-3-642-03986-7_19
  8. J.J. Gibson, The ecological approach to visual perception, Houghton Mifflin, Boston, 1979
  9. J. Norman, "Ecological psychology and the two visual systems: not to worry", Ecological Psychology, vol.13, no.2, pp.135-145, 2001 https://doi.org/10.1207/S15326969ECO1302_6
  10. S.-H. Hsiao, C.F. Hsu, and Y.-T. Lee, "An online affordance evaluation model for product design", Design Studies, vol.33, no.2, pp.126-159, 2011
  11. R. Detry, E. Baseski, M. Popovic, Y. Touati, N. Kruger, O. Kroemer, J. Peters, and J. Piater, "Learning object-specific grasp affordance densities", IEEE 8th Int. Conf. Development and Learning, pp.1-7, 2009
  12. A. Stoytchev, "Behavior-grounded representation of tool affordances", Proc. IEEE Int. Conf. Robotics and Automation, pp.3060-3065, 2005
  13. K. MacDorman, "Responding to affordances: learning and projecting a sensorimotor mapping", Proc. IEEE Int. Conf. Robotics and Automation, pp.3253-3259, 2000
  14. I. Cos-Aguilera, L. Canamero, and G. Hayes, "Motivation-driven learning of object affordances: first experiments using a simulated Khepera robot", Proc. 9th Int. Conf. Cognitive Modeling, pp.57-62, 2003
  15. G. Fritz, L. Paletta, M. Kumar, G. Dorffner, R. Breithaupt, and E. Rome, "Visual learning of affordance based cues", Proc. 9th. Int. Conf. the Simulation of Adaptive Behavior, LNAI, vol.4095, pp.52-64, 2006
  16. P. Fitzpatrick, G. Metta, L. Natale, A. Rao, and G. Sandini, "Learning about objects through action-initial steps towards artificial cognition", Proc. IEEE Int. Conf. Robotics and Automation, pp.3140-3145, 2003
  17. V.N. Papudesi and M. Huber, "Learning behaviorally grounded state representations for reinforcement learning robots", Proc. Int. Conf. Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, 2006
  18. L. Stark and K. W. Bowyer, "Function-based recognition for multiple object categories", Image Understanding, vol.59, no.10, pp.1-21, 1994
  19. E. Rivlin, S. J. Dickinson, and A. Rosenfeld, "Recognition by functional parts", Computer Vision and Image Understanding, vol.62, no.2, pp.164-176, 1995 https://doi.org/10.1006/cviu.1995.1048
  20. L. Bogoni and R. Bajcsy, "Interactive recognition and representation of functionality", Computer Vision and Image Understanding, vol.62, no.2, pp.194-214, 1995 https://doi.org/10.1006/cviu.1995.1050
  21. M. Wunstel and R. Moratz, "Automatic Object Recognition within an Office Environment", Proc. 1st IEEE Canadian Conf. Computer and Robot Vision, pp.104-109, 2004
  22. M.A. Lewis, "Perception Driven Robot Locomotion", Journal Robot Society of Japan, vol.20, no.3, pp.51-56, 2002 https://doi.org/10.7210/jrsj.20.51
  23. T.L. Saaty, The analytic hierarchy process: planning, priority setting, resource allocation (decision making series), McGraw-Hill, 1980
  24. A. Neudorfer and K. Tanaka, Design of Safety Machinery in Accordance with International Standards, Nippon HyoronSha Co. Publisher, 2002 (in Japanese)
  25. Reference Manual of Anthropometry in Ergonomic Designing, edited by National Institute of Bioscience and Human-Technology, 1996 (in Japanese)