Toward a robot that acquires logical recognition of space
AbstractFor cooperation between robot and human being, robot should have logical recognition about space. For example, if a robot such as a housekeeping robot can recognize the arrangement structure of the furnitures and the concept of ``a room'', it will be useful information for asking the robot for work. Therefore, we aim for the robot to acquire the relationship between locations while moving. So, expecting that the robot gets the recognition that ``I have gotten out of the room'', we performed an initial stage experiment that a robot leaves the room using knowledge of the relationship between the entrance of the room and the door. This paper describes the insights obtained from this experiment.
M. Fujita, Y. Goto, N. Nide, K. Satoh, and H. Hosobe. Autonomous control of mobile robots using logical representation of map and inference of location. In Proc. of IEEE ICA2016, pages 78–81, 2016. Available at http://blackknight.ics.nara-wu.ac.jp/~kuma/paper/ica2016.pdf.
M. Fujita, Y. Goto, N. Nide, K. Satoh, and H. Hosobe. Autonomous control of mobile robots using logical representation of map and inference of location. IEICE Transactions on Information and Systems, submitted. Available at http://blackknight.ics.nara-wu.ac.jp/~kuma/paper/ieice2017.pdf.
A. S. Rao and M. P. Georgeff. Modeling Rational Agents within a BDI-Architecture. In M. N. Huhns and M. P. Singh, editors, Readings in Agents, pages 317–328. Morgan Kaufmann, San Francisco, 1997.
M. E. Bratman. Intention, Plans, and Practical Reason. Harvard University Press, 1987.
R. H. Bordini, J. F. H¨ubner, and M. Wooldridge. Programming Multi-Agent Systems in AgentSpeak using Jason. John Wiley & Sons, 2007.
M. Fujita, H. Katayama, N. Nide, and S. Takata. BDI robots who adapt to the diversity of the real world. IPSJ Transactions on MPS, 5(1):50–64, 2012. (In Japanese).
E. Fern´andez, L. S. Crespo, A. Mahtani, and A. Martinez. Learning ROS for Robotics Programming — second edition. Packt Publishing, 2015.
M. Fujita, Y. Goto, N. Nide, K. Satoh, and H. Hosobe. Logic-based and robust decision making for robots in real world. In Proc. of AAMAS '14, pages 1685–1686, 2014.
M. Fujita, Y. Goto, N. Nide, K. Satoh, and H. Hosobe. An architecture for autonomously controlling robot with embodiment in real world. In Proc. of Knowledge Representation and Reasoning in Robotics (workshop at ICLP 2013), pages 59–71, 2013.
Hokuyo automatic co., ltd. 3D-LIDAR YVT-X0002. http://www.hokuyo-aut.jp/02sensor/07scanner/3d_urg.html. Viewed on Mar 30, 2017.
S. Zhang, M. Sridharan, M. Gelfond, and J. Wyatt. An architecture for knowledge representation and reasoning in robotics. In Proc. of 15th International Workshop on Non-Monotonic Reasoning, pages 233–241, 2014.
A. N¨uchter and J. Hertzberg. Towards semantic maps for mobile robots. Robotics and Autonomous Systems, 56(11):915–926, 2008.
A. N¨uchter, K. Lingemann, J. Hertzberg, and H. Surmann. 6D SLAM — 3D mapping outdoor environments. Journal of Field Robotics, 24(8-9):699–722, 2007.
M. Ghallab, D. S. Nau, and P. Traverso. Automated Planning: Theory and Practice, Morgan Kaufmann Publishers Inc., 2004.
G. Lidoris, F. Rohrmu¨uller, D. Wollherr, and M. Buss. The autonomous city explorer (ACE) project — mobile robot navigation in highly populated urban environments. In Proc. of IEEE ICRA2009, pages 1416–1422, 2009.
C. Brandstatter, S. Schaat, A. Wendt, and M. Fittner. How agents use breadcrumbs to find their way. Journal of Computers, 12(1):89–96, 2017.