DOI QR코드

DOI QR Code

Safe Navigation of a Mobile Robot Considering the Occluded Obstacles

가려진 동적 장애물을 고려한 이동로봇의 안전한 주행기술개발

  • Published : 2008.02.01

Abstract

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.

Keywords

References

  1. Konolige, 'A gradient method for realtime robot control,' Proc. of the IEEE/RSJ Conf. on Intelligent Robots and Systems, Takamatsu, Japan, pp. 639-646, 2000
  2. D. Fox, W. Burgard, and S. Thrun, 'The dynamic window approach to collision avoidance,' IEEE Robotics and Automation Magazine, vol. 4, no. 1, pp. 23-33, 1997 https://doi.org/10.1109/100.580977
  3. O. Brock and O. Khatib, 'High speed navigation using the global dynamic window approach,' In Proceedings of the International Conference on Robotics and Automation, vol. 1, pp. 341-346, 1999
  4. M. Sadou, V. Polotski, and P. Cohen, 'Occlusions in obstacle detection for safe navigation,' IEEE Intelligent Vehicle Symposium, pp. 716-721, 2004
  5. W. Chung, G. Kim, and M. Kim 'Development of the Multi- Functional Indoor Service Robot PSR Systems,' Autonomous Robots (To appear. Published online at http://dx.doi.org/10.1007/ s10514-006-9001-z)
  6. K. M. Krishna, R. Alami, and T. Simeon, 'Safe proactive plans and their execution,' Robotics and Autonomous Systems, vol. 54, pp. 244-255, 2006 https://doi.org/10.1016/j.robot.2005.10.008
  7. M. Bennewitz, W. Burgard, G. Cielniak, and S. Thrun. 'Learning motion patterns of people for compliant motion,' International Journal of Robotics Research, 24(1), 2005
  8. W. Burgard, A. B. Cremers, D. Fox, G. Lakemeyer, D. Hahnel, D. Schulz, and S. Thrun. 'Real robots for the real world--the RHINO museum tour-guide project,' In Proc. of the AAAI 1998 Spring Symposium on Integrating Robotics Research: Taking the Next Leap, 1998
  9. A. Mandow, V. F. Mufloz, R. Fernandez, and A. G.-Cerezo. 'Dynamic speed planning for safe navigation,' In Proc. of the int. Conference on Intelligent Robots and Systems(IROS), 1997
  10. F. Dellaeert, D. Fox, W. Burgard, and S. Thrun, 'Monte carlo localization for mobile robots,' In Proc. IEEE Int..Conference on Robotics and Automation., Detroit, MI, 1999, pp. 1322-1328
  11. R. Alami, T. simeon, and K. M. Krishna, 'On the influence of sensor capacities and environment dynamics onto collision free motion plans,' In Proc. IEEE/RSJ Int. Conference on Intelligent Robots and Systems, EPFL, Switzerland, 2002