Environmental Modeling Based on Ultrasonic Ranging

Abstract:

In order to deal with the conflict of the robot high-performance implementing the task in an uncertain environment, environmental modeling method based on ultrasonic ranging was adopted. By the complex environmental modeling mean of combining the methods of grid and geometry, relying the measurement data of the adjacent multi-ultrasonic and the correlation among the data, the environmental modeling was established effectively. The modeling characteristics analysis showed that: the robot can easily make obstacle avoidance, path planning and decision-making in the grid-based modeling. The accuracy of the modeling is high, and it can detect and update the complex regional expediently. The environmental modeling based on ultrasonic ranging can effectively solve the problem of mobile robot implementing the tasks efficiently in the actual complex environment.

• Periodical: Applied Mechanics and Materials (Volumes 341-342)
• Pages: 1210-1215
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.341-342.1210
• Online since: July 2013
• Authors: Jun Hui Wu, Tong Di Qin, Hui Ping Si, Jie Chen, Kai Yan Lin, Chi Bin Zhang
• Keywords: Environment Modeling, Grid-Based Map, Mobile Robot, Sensor, Ultrasonic Ranging

References

[1] M. Kondo, K. Kimura. Collision avoidance using afree space enumeration method based on grid expansion. Advanced Robotics, 3(3), 1989, pp.159-175.

DOI: 10.1163/156855389x00073

[2] Z.Q. Ma, R. Zeng. Mobile robot real-time navigation and obstacle avoidance based on the grid method. Robot, 18(6), 1996, pp.344-348.

[3] P. Trahanias. Visual Recognition of Workspace Landmarks for Topological Navigation. Autonomous Robotics, 7(2), 1999, pp.143-158.

[4] D. Avis, B.K. Bhattacharya. Algorithms for Computing d-dimensional Voronoi Diagrams and Their Duals. Advances in Computing Research. 1 (1983), pp.159-180.

[5] H. Choset, K. Nagatani, A. Rizzi. Sensor based planning: Using a honing strategy and local map method to implement the generalized Voronoi graph. In Proc. SPIE Conf. Systems and Manufacturing, (1997).

DOI: 10.1117/12.299555

[6] G. Dudek, M. Jenkin. Computational principles of mobile robotics. Cambridge Univ Press，2000, pp.132-145.

[7] Lozano-Perez T. Automatic planning of manipulator transfer mobement. IEEE Trans on Systems, Man and Cybernetics, 11(10), 1981, pp.681-698.

DOI: 10.1109/tsmc.1981.4308589

[8] Lozano-Perez T. Spatial planning: A configuration space approach. IEEE Trans on Computers, 32(2), 1983, pp.108-120.

DOI: 10.1109/tc.1983.1676196

[9] E. Fabrizi, A. Saffioti. Extracting Topology-Based Maps from Gridmaps. In Proc. Of the IEEE Int. Conf. on Robotics and Automation(ICRA), 29(2000), pp.72-78.

DOI: 10.1109/robot.2000.846479

[10] Habib M. K, Asama H. Efficient method to generate collision free path for autonomous mobile robot based on new free space structuring approach. Proc. IEEE/RSJ IROS, 1991, pp.563-567.

DOI: 10.1109/iros.1991.174534

[11] S. d. Sun, Y.B. Qu. The applied research of the genetic algorithms in robot path planning. Northwestern Polytechnical University, 16(1), 1998, pp.79-83.

[12] Chatila R. Path Planning and Environment Learning in a Mobile Robot System. Proc of the European Conf on AI, (1982).

[13] J. Kim, R. Pearce, N. Amato. Robust Geometric-Based Localization in Indoor Environments Using Sonar Range Sensors. In Proc. Of the IEEE Int. Conf. on Intelligent Robots and Systems(IROS), 2002, pp.421-426.

DOI: 10.1109/irds.2002.1041426

[14] N.Q. Liu, G.M. Zhou. A new method based on multi-ultrasonic information establishing a new environmental model precisely. 27(3), 2005, pp.261-266.

[15] Moravec H P. Sensor Fusion in Certain Grids for Mobile Robots. A I Magazine, 9(2), 1988, pp.61-74.