ABSTRACT
Environment attributes are perceived or remembered differently according to the perspective used. In this study, two different perspectives, a survey perspective and a route perspective, are explained and discussed. This paper proposes an approach for modeling human environments from a route perspective, which is the perspective used when a human navigates through the environment. The process for route perspective semi-autonomous data extraction and modeling by a mobile robot equipped with a laser sensor and a camera is detailed. Finally, as an example of a route perspective application, a route direction robot was developed and tested in a real mall environment. Experimental results show the advantages of the proposed route perspective model compared with a survey perspective approach. Moreover, the route model is comparable to the performance of an expert person giving route guidance in the mall.
Supplemental Material
- The Tesseract OCR engine, Retrieved 2010, Aug. 23, http://code.google.com/p/tesseract-ocr/.Google Scholar
- Beeson, P., Jong, N. K. and Kuipers, B., 2005, Towards Autonomous Topological Place Detection Using the Extended Voronoi Graph, IEEE Int. Conf. on Robotics and Automation (ICRA2005), pp. 4373--4379.Google Scholar
- Berlin, M., Gray, J., Thomaz, A. L. and Breazeal, C., 2006, Perspective Taking: An Organizing Principle for Learning in Human-Robot Interaction, National Conf. on Artificial Intelligence (AAAI2006), pp. 1444--1450. Google ScholarDigital Library
- Besl, P. and McKay, N., 1992, A method for Registration of 3-D Shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, pp. 239--256. Google ScholarDigital Library
- Brunskill, E., Kollar, T. and Roy, N., 2007, Topological Mapping Using Spectral Clustering and Classification, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS2007), pp. 3491--3496.Google Scholar
- Choset, H. and Burdick, J., 1995, Sensor Based Planning, Part I: The Generalized Voronoi Graph, Proceedings of the 1995 IEEE International Conference on Robotics and Automation (ICRA '95), pp. 1649--1655.Google Scholar
- D. Fox, W. B., and S. Thrun, 1999, Markov localization for mobile robots in dynamic environments, Journal of Artificial Intelligence Research, vol. 11, pp. 391--427.Google ScholarCross Ref
- Daniel, M.-P., Tom, A., Manghi, E. and Denis, M., 2003, Testing the Value of Route Directions Through Navigational Performance, Spatial Cognition & Computation, vol. 3, pp. 269--289.Google ScholarCross Ref
- Dissanayake, M. W. M. G., Newman, P., Clark, S., Durrant-Whyte, H. F. and Csorba, M., 2001, A solution to the simultaneous localization and map building (SLAM) problem, IEEE Transactions on Robotics and Automation, vol. 17, pp. 229 - 241.Google ScholarCross Ref
- Elfes, A., 1989, Using Occupancy Grids for Mobile Robot Perception and Navigation, Computer, vol. 22, pp. 46--57. Google ScholarDigital Library
- Garling, T. and Evans, G. W., 1991, Environment, Cognition, and Action: An Integrated Approach, New York : Oxford University Press.Google Scholar
- Gockley, R., Forlizzi, J. and Simmons, R., 2007, Natural Person-Following Behavior for Social Robots, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2007), pp. 17--24. Google ScholarDigital Library
- Grisetti, G., Stachniss, C. and Burgard, W., 2007, Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters, IEEE Transactions on Robotics, vol. 23, pp. 34--46. Google ScholarDigital Library
- Hato, Y., Satake, S., Kanda, T., Imai, M. and Hagita, N., 2010, Pointing to Space: Modeling of Deictic Interaction Referring to Regions, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2010), pp. 301--308. Google ScholarDigital Library
- Kendon, A., 2004, Gesture: Visible Action as Utterance, Cambridge University Press.Google ScholarCross Ref
- Kita, S., 2003, Interplay of gaze, hand, torso orientation and language in pointing, in Pointing: Where Language, Culture, and Cognition Meet, S. Kita ed., pp. 307--328.Google Scholar
- Klippel, A., Hansen, S., Davies, J. and Winter, S., 2005, A High-Level Cognitive Framework For Route Directions, The National Biennial Conference of the Spatial Science Institute,Google Scholar
- Kollar, T., Tellex, S., Roy, D. and Roy, N., 2010, Toward Understanding Natural Language Directions, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2010), pp. 259--266. Google ScholarDigital Library
- Kopp, S., Tepper, P. A., Ferriman, K., Striegnitz, K. and Cassell, J., 2008, Trading spaces: How humans and humanoids use speech and gesture to give directions, in Conversational informatics: An engineering approach, T. Nishida ed., pp. 133--160.Google Scholar
- Levenshtein, V. I., 1966, Binary codes capable of correcting deletions, insertions, and reversals, Soviet Physics Doklady, vol. 10, pp. 707--710.Google Scholar
- Matuszek, C., Fox, D. and Koscher, K., 2010, Following Directions Using Statistical Machine Translation, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2010), pp. 251--258. Google ScholarDigital Library
- Montello, D. R., 1997, The Perception and Cognition of Environmental Distance: Direct Sources of Information, Proceedings of the International Conference on Spatial Information Theory: A Theoretical Basis for GIS, pp. 297--311. Google ScholarDigital Library
- Mozos, Ó. M., Triebel, R., Jensfelt, P., Rottmann, A. and Burgard, W., 2007, Supervised semantic labeling of places using information extracted from sensor data, Robotics and Autonomous Systems, vol. 55, pp. 391--402. Google ScholarDigital Library
- Nothegger, C., Winter, S. and Raubal, M., 2004, Selection of Salient Features for Route Directions, Spatial Cognition & Computation, vol. 4, pp. 113--136.Google ScholarCross Ref
- Okuno, Y., Kanda, T., Imai, M., Ishiguro, H. and Hagita, N., 2009, Providing Route Directions: Design of Robot's Utterance, Gesture, and Timing, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2009), pp. 53--60. Google ScholarDigital Library
- Ono, T., Imai, M. and Ishiguro, H., 2001, A Model of Embodied Communications with Gestures between Humans and Robots, Annual Meeting of the Cognitive Science Society (CogSci2001), pp. 732--737.Google Scholar
- Peltason, J., Siepmann, F. H. K., Spexard, T. P., Wrede, B., Hanheide, M. and Topp, E. A., 2009, Mixed-Initiative in Human Augmented Mapping, IEEE Int. Conf. on Robotics and Automation (ICRA2009), pp. 2146--2153. Google ScholarDigital Library
- Sisbot, E. A., Marin-Urias, L. F., Alami, R. and Simeon, T., 2007, A Human Aware Mobile Robot Motion Planner, IEEE Transactions on Robotics, vol. 23, pp. 874--883. Google ScholarDigital Library
- Spexard, T., Li, S., Wrede, B., Fritsch, J., Sagerer, G., Booij, O., Zivkovic, Z., Terwijn, B. and Kröse, B., 2006, BIRON, where are you? Enabling a robot to learn new places in a real home environment by integrating spoken dialog and visual localization, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS2006), pp. 934--940.Google Scholar
- Striegnitz, K., Tepper, P., Lovett, A. and Cassell, J., 2005, Knowledge Representation for Generating Locating Gestures in Route Directions, Workshop on Spatial Language and Dialogue (5th Workshop on Language and Space),Google Scholar
- Thrun, S., Burgard, W. and Fox, D., 2005, Probabilistic Robotics (Intelligent Robotics and Autonomous Agents), The MIT Press. Google ScholarDigital Library
- Topp, E. A. and Christensen, H. I., 2006, Topological Modelling for Human Augmented Mapping, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS2006), pp. 2257--2263.Google Scholar
- Trafton, J. G., Cassimatis, N. L., Bugajska, M. D., Brock, D. P., Mintz, F. E. and Schultz, A. C., 2005, Enabling Effective Human-Robot Interaction Using Perspective-Taking in Robots, IEEE Trans. on Systems, Man, and Cybernetics. Part A: Systems and Humans, vol. 35, pp. 460- 470. Google ScholarDigital Library
- Tversky, B., 1993, Cognitive maps, cognitive collages, and spatial mental models, Spatial Information Theory A Theoretical Basis for GIS, pp. 14--24.Google ScholarCross Ref
- Vasudevan, S., Gachter, S., Nguyen, V. and Siegwart, R., 2007, Cognitive maps for mobile robots-an object based approach, Robotics and Autonomous Systems, vol. 55, pp. 359--371 Google ScholarDigital Library
Index Terms
- Modeling environments from a route perspective
Recommendations
Optimal Route Reflection Topology Design
LANC '18: Proceedings of the 10th Latin America Networking ConferenceAutonomous Systems (ASes) exchange routing information about networks they can reach in the Internet, and the most widely extended way to connect them is by means of Border Gateway Protocol (BGP) sessions. ASes set up external BGP (eBGP) sessions ...
Designing optimal iBGP route-reflection topologies
NETWORKING'08: Proceedings of the 7th international IFIP-TC6 networking conference on AdHoc and sensor networks, wireless networks, next generation internetThe Border Gateway Protocol (BGP) is used today by all Autonomous Systems (AS) in the Internet. Inside each AS, iBGP sessions distribute the external routes among the routers. In large ASs, relying on a full-mesh of iBGP sessions between routers is not ...
Aligning spatial perspective in route descriptions
SC'10: Proceedings of the 7th international conference on Spatial cognitionSpatial perspective refers to the use of reference systems in extended spatial descriptions and wayfinding. Variable viewpoints, conceptualizations, and reference terms may lead speakers to describe an environment and movement in it in a route ...
Comments