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Performance evaluation of pure-motion tasks for mobile robots with respect to world models

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Abstract

The evaluation of the performance of robot motion methods and systems is still an open challenge, although substantial progress has been made in the field over the years. On the one hand, these techniques cannot be evaluated off-line, on the other hand, they are deeply influenced by the task, the environment and the specific representation chosen for it. In this paper we concentrate on “pure-motion tasks”: tasks that require to move the robot from one configuration to another, either being an independent sub-task of a more complex plan or representing a goal by itself. After characterizing the goals and the tasks, we describe the commonly-used problem decomposition and different kinds of modeling that can be used, from accurate metric maps to minimalistic representations. The contribution of this paper is an evaluation framework that we adopt in a set of experiments showing how the performance of the motion system can be affected by the use of different kinds of environment representations.

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References

  • Amigoni, F., & Gasparini, S. (2008). Analysis of methods for reducing line segments in maps: towards a general approach. In Proc. of IEEE/RSJ int. conf. on robots and intelligent systems (IROS) (pp. 2896–2901).

  • Beeson, P., Jong, N. K., & Kuipers, B. (2005). Towards autonomous topological place detection using the extended Voronoi graph. In Proc. of the IEEE int. conf. on robotics and automation (ICRA) (pp. 4373–4379). Barcelona, Spain.

  • Bhattacharya, P., & Gavrilova, M. (1991). Roadmap-based path planning. In IEEE robotics and automation magazine (pp. 58–66).

  • Borenstein, J. (1991). The vector field histogram-fast obstacle avoidance for mobile robots. IEEE Transactions on Robotics and Automation, 7(3), 278–288.

    Article  Google Scholar 

  • Brock, O., & Khatib, O. (1999). High-speed navigation using the global dynamic window approach. In IEEE int. conf. on robotics and automation (ICRA) (pp. 341–346).

  • Bruce, J., & Veloso, M. (2002). Real-time randomized path planning for robot navigation. In Proceedings of IROS-2002, Switzerland, October 2002.

  • Calisi, D., Farinelli, A., Iocchi, L., & Nardi, D. (2005). Autonomous navigation and exploration in a rescue environment. In Proceedings of IEEE international workshop on safety, security and rescue robotics (SSRR) (pp. 54–59). Kobe, Japan. ISBN 0-7803-8946-8.

  • Calisi, D., Iocchi, L., & Nardi, D. (2008). A unified benchmark framework for autonomous mobile robots and vehicles motion algorithms (MoVeMA benchmarks). In RSS workshop on experimental methodology and benchmarking, Zurich, Switzerland.

  • Censi, A., Calisi, D., De Luca, A., & Oriolo, G. (2008). A Bayesian framework for optimal motion planning with uncertainty. In Proc. of the IEEE int. conference on robotics and automation (ICRA) (pp. 1798–1805). doi:10.1109/ROBOT.2008.4543469.

  • Choset, H., & Nagatani, K. (2001). Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization. IEEE Transactions on Robotics and Automation, 17, 125–137.

    Article  Google Scholar 

  • Collet, T., MacDonald, B., & Gerkey, B. (2005). Player 2.0: Toward a practical robot programming framework. In Proc. of the Australasian conf. on robotics and automation (ACRA 2005).

  • Coolidge, J. (1952). The unsatisfactory story of curvature. The American Mathematical Monthly, 59(6), 375–379.

    Article  MATH  MathSciNet  Google Scholar 

  • Fernández, J., Sanz, R., Benayas, J., & Diéguez, A. (2004). Improving collision avoidance for mobile robots in partially known environments: the beam curvature method. Robotics and Autonomous Systems, 46(4), 205–219.

    Article  Google Scholar 

  • Filliat, D. (2008). Interactive learning of visual topological navigation. In IEEE/RSJ international conference con intelligent robots and systems (IROS) (pp. 248–254). Nice, France.

  • Fox, D., Burgard, W., & Thrun, S. (1997). The dynamic window approach to collision avoidance. IEEE Robotics & Automation Magazine, 4(1), 23–33. doi:10.1109/100.580977. URL: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=580977.

    Article  Google Scholar 

  • Guo, Y., Qu, Z., & Wang, J. (2003). A new performance-based motion planner for nonholonomic mobile robots. In E. Messina & A. Meystel (Eds.), Proc. of int. workshop on performance metrics for intelligent systems workshop (PerMIS).

  • Gupta, K. K. (1998). Overview and state of the art. In K. Gupta & A. del Pobil (Eds.), Practical motion planning in robotics: current approaches and future directions (pp. 3–8). New York: Wiley.

    Google Scholar 

  • Hwang, Y. K., & Ahuja, N. (1992). Gross motion planning: a survey. ACM Computing Surveys, 24(3), 219–291. ISSN 0360-0300. doi:10.1145/136035.136037.

    Article  Google Scholar 

  • Koren, Y., & Borenstein, J. (1991). Potential field methods and their inherent limitations for mobile robot navigation. In Proceedings of the IEEE conference on robotics and automation (ICRA) (pp. 1398–1404). URL: http://www-personal.umich.edu/~johannb/mypapers.htm.

  • Kostov, V., & Degtiariova-Kostova, E. (1995). The planar motion with bounded derivative of the curvature and its suboptimal paths. Acta Mathematica Universitatis Comeianae, 64, 185–226. URL: http://cgal.inria.fr/Publications/1995/KD95b.

    MATH  MathSciNet  Google Scholar 

  • Kuipers, B. (1985). The map-learning critter. Technical report, University of Texas at Austin.

  • Kuipers, B., & Byun, Y.-T. (1991). A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations. Journal of Robotics and Autonomous Systems, 8, 47–63. URL: citeseer.csail.mit.edu/kuipers91robot.html.

    Article  Google Scholar 

  • Latombe, J. C. (1991). Robot motion planning. Dordrecht: Kluwer Academic.

    Google Scholar 

  • Lynch, K. (1960). The image of the city. Cambridge: MIT Press.

    Google Scholar 

  • Minguez, J., & Montano, L. (2004). Nearness diagram (nd) navigation: Collision avoidance in troublesome scenarios. IEEE Transactions on Robotics and Automations, 20(1), 45–59.

    Article  Google Scholar 

  • Minguez, J., Montano, L., Simeon, T., & Alami, R. (2001). Global nearness diagram (gnd) navigation. In Proceedings of the IEEE international conference on robotics and automation (ICRA) (vol. 1, pp. 33–39).

  • Minguez, J., Montano, L., & Santos-Victor, J. (2006). Abstracting vehicle shape and kinematic constraints from obstacle avoidance methods. Autonomous Robots, 20(1), 43–59. ISSN 0929-5593.

    Article  Google Scholar 

  • Minguez, J., Lamiraux, F., & Laumond, J.-P. (2008). Motion planning and obstacle avoidance. In B. Siciliano & O. Khatib (Eds.), Springer handbook of robotics. Berlin: Springer. doi:10.1007/978-3-540-30301-5.

    Google Scholar 

  • Mjolsness, R. C., & Swartz, B. (1987). Some plane curvature approximations. Mathematics of Computation, 49(179), 215–230.

    Article  MATH  MathSciNet  Google Scholar 

  • Montemerlo, M., Thrun, S., Koller, D., & Wegbreit, B. (2002). FastSLAM: a factored solution to the simultaneous localization and mapping problem. In Proc. of the conf. American association for artificial intelligence (AAAI), Edmonton, Canada.

  • Muñoz, N., Valencia, J., & Londoño, N. (2007). Evaluation of navigation of an autonomous mobile robot. In Proc. of int. workshop on performance metrics for intelligent systems workshop (PerMIS) (pp. 15–21).

  • Nilsson, N. J. (1969). A mobile automaton: an application of artificial intelligence techniques. In Proc. of int. joint conf. on artificial intelligence (IJCAI) (pp. 509–520).

  • Ozguner, U., Stiller, C., & Redmill, K. (2007). Systems for safety and autonomous behavior in cars: The DARPA Grand Challenge experience. Proceedings of the IEEE, 95(2), 397–412. ISSN 0018-9219. doi:10.1109/JPROC.2006.888394.

    Article  Google Scholar 

  • Raño, I., & Minguez, J. (2006). Steps towards the automatic evaluation of robot obstacle avoidance algorithms. In Proc. of workshop of benchmarking in robotics, in the IEEE/RSJ int. conf. on intelligent robots and systems (IROS).

  • Rawlinson, D., & Jarvis, R. (2008). Topologically-directed navigation. Robotica, 26(02), 189–203. doi:10.1017/S026357470700375X.

    Article  Google Scholar 

  • Reif, J. H. (1979) Complexity of the mover’s problem and generalization. In Proceedings of the 20th IEEE symposium on foundations of computer sciences (FOCS) (pp. 421–427).

  • Rosenblatt, J. (1997). DAMN: A distributed architecture for mobile navigation. Journal of Experimental and Theoretical Artificial Intelligence, 9(1), 339–360.

    Article  MathSciNet  Google Scholar 

  • Sack, D., & Burgard, W. (2004). A comparison of methods for line extraction from range data. In Proc. of the 5th IFAC symposium on intelligent autonomous vehicles (IAV).

  • Shmaglit, A., Rinat, K., Brand, Z., Fischler, A., & Velger, M. (2006). Autonomous vehicle control and obstacle avoidance concepts oriented to meet the challenging requirements of realistic missions. In International conference on control, automation, robotics and vision (ICARCV) (pp. 1–6). doi:10.1109/ICARCV.2006.345219.

  • Simmons, R. (1996). The curvature-velocity method for local obstacle avoidance. In Proceedings of IEEE international conference on robots and automation (vol. 4, pp. 3375–3382).

  • Stachniss, C., & Burgard, W. (2002). An integrated approach to goal-directed obstacle avoidance under dynamic constraints for dynamic environments. In Proc. of the IEEE/RSJ int. conf. on intelligent robots and systems (IROS).

  • Taïx, M., Malti, A. C., & Lamiraux, F. (2008). Planning robust landmarks for sensor based motion. In H. Bruyninckx, L. Preucil, & M. Kulich (Eds.), Springer tracts in advanced robotics : Vol. 44. European robotics symposium (EUROS) (pp. 195–204). Berlin: Springer. ISBN 978-3-540-78315-2. URL: http://dblp.uni-trier.de/db/conf/euros/euros2008.html#TaixML08. doi:10.1007/978-3-540-78317-6_20.

    Chapter  Google Scholar 

  • Tomomi, K., Jun, O., Rie, K., Takahisa, M., Tamio, A., Tsuyoshi, U., & Tsuyoshi, N. (2003). Path planning for a mobile robot considering maximum curvature, maximum curvature derivative, and curvature continuity. Transactions of the Japan Society of Mechanical Engineers, 69(688), 3269–3276.

    Google Scholar 

  • Ulrich, I., & Borenstein, J. (1998). VFH+: Reliable obstacle avoidance for fast mobile robots. In Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 1572–1577).

  • Ulrich, I., & Borenstein, J. (2000). VFH*: Local obstacle avoidance with look-ahead verification. In Proceedings of the 2000 IEEE international conference on robotics and automation (ICRA) (pp. 2505–2511).

  • Werner, F., Gretton, C., Maire, F., & Sitte, J. (2008). Induction of topological environment maps from sequences of visited places. In IEEE/RSJ international conference con intelligent robots and systems (IROS) (pp. 2890–2895).

  • Yun, J., & Miura, J. (2008). Quantitative measure for the navigability of a mobile robot using rough maps. In IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 3458–3464). Nice, France.

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  1. Dipartimento Informatica e Sistemistica, “Sapienza” University of Rome, Via Ariosto, 25, Roma, 00185, Italy

    Daniele Calisi & Daniele Nardi

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  1. Daniele Calisi
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  2. Daniele Nardi
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Correspondence to Daniele Calisi.

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Calisi, D., Nardi, D. Performance evaluation of pure-motion tasks for mobile robots with respect to world models. Auton Robot 27, 465–481 (2009). https://doi.org/10.1007/s10514-009-9150-y

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