Design on Hierarchical Testing System for Unmanned Ground Vehicles

Abstract:

The test system for technical abilities of unmanned vehicles is gradually developed from the single test to comprehensive test. The pre-established test and evaluation system can promote the development of unmanned ground vehicles. The 2009 Future Challenge: Intelligent Vehicles and Beyond (FC’09) pushed China's unmanned vehicles out of laboratories. This paper proposed to design a more scientific and comprehensive test system for future competitions to better guide and regulate the development of China's unmanned vehicles. According to the design idea of stage by stage and level by level, the hierarchical test content from simple to advanced, from local to overall is designed. Then the hierarchic test environment is established according to the levels of test content. The test method based on multi-platform and multi-sensor is put forward to ensure the accuracy of test results. The testing criterion framework is set up to regulate future unmanned vehicle contests and to assess the unmanned vehicles scientifically and accurately.

• Periodical: Advanced Materials Research (Volume 346)
• Pages: 817-822
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.346.817
• Online since: September 2011
• Authors: Xin Li, Guang Ming Xiong, Yang Sun, Shao Bin Wu, Jian Wei Gong, Hui Yan Chen, Li Gao
• Keywords: Hierarchic Test Content Design, Hierarchic Test Environment Design, Standard Test, Test Method, Unmanned Ground Vehicle

References

[1] Tsugawa. S. Vision-Based Vehicles in Japan: Machine Vision Systems and Driving Control Systems[C]. IEEE Trans. on Industrial Electronics, 41 (4): PP. 398-405, (1994).

DOI: 10.1109/41.303790

[2] Andresen E.P., et al. Visual algorithms for autonomous navigation, Proc. of IEEE International Conf. on Robotics and Automation[C], PP. 856-861, (1985).

[3] Thorpe. C, et al. Vision and navigation for the Carnegie-Mellon Navlab [J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 10(3): 362-373, (1988).

DOI: 10.1109/34.3900

[4] Baten. S, et al. Techniques for autonomous, off-road navigation [J]. IEEE Intelligent systems and Their Applications, 13(6): PP. 57-65, (1998).

DOI: 10.1109/5254.736003

[5] Bertozzi. M, Broggi. A, Fascioli. A. Vision-based intelligent vehicles: State of the art and perspectives [J]. Robotics and Autonomous Systems, 32: PP. l-16, (2000).

DOI: 10.1016/s0921-8890(99)00125-6

[6] Bertozzi. M, Broggi. A. GOLD: a Parallel Real-time Stereo Vision System for Generie Obstacle and Lane Detection[C]. IEEE Trans, on Image Processing, 7(1): PP. 62-81, (1998).

DOI: 10.1109/83.650851

[7] Thorpe. C, et al. Smart Cars: The CMU Navlab[C]. Proe. Of world Med., (1993).

[8] Shoemaker. C. M, Bomstein. J. A. Overview of the Demo III UGV Program[C]. Part of the SPIE Conf. on Robotic and Semi-Robotic Ground vehicle Technology, PP. 202-211, (1998).

DOI: 10.1117/12.317547

[9] http: /www. darpa. mil/grandchallenge/index. asp.

[10] http: /www. sapro. com. au/smartdemo/smartdemo2005. htm/. (2006).

[11] http: /www. elrob2006. org.

[12] http: /ccvai. xjtu. edu. cn/news. do?method=getdetails&id=33.

[13] http: /www. nsfc. gov. cn/Portal0/InfoModule_375/31231. htm.

[14] http: /www. myriichauto. net/viewthread. php?tid=11646.

[15] http: /www. hf. cas. cn/xwzx/jqyw/201010/t20101021_2990756. html.