지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.6
- 수록면
- 485 - 491 (7page)
- DOI
- 10.5302/J.ICROS.2019.19.0058
이용수
초록· 키워드
오류제보하기
Mobile robots and autonomous vehicles are used for many areas, including exploration, delivery, rescue, and even home cleaning. The way that the robot perceives the environment plays a key role because the environmental model can be used for localization and mapping. Examples of environmental model generation tools are simultaneous localization and mapping (SLAM) that was developed for robotics and 3D maps that are usually generated from vision system data. In parallel, artificial intelligence (AI) has supplemented human reasoning and has affected various fields as researchers developed the computer hardware and algorithms. While the learning capability of AI has been used for environment perception, the success of AI is dependent on input parameter selection, structure, and training data. In this paper, we used spatial gradient information as additional inputs and introduced a perturbation/correlation-based spatial gradient estimation, which is very robust to noise since it is performed as an integration instead of the typical approach of calculating the gradient. Our experimental results show the effectiveness of the spatial gradient estimation. We presented an example to illustrate the improved perception from the additional gradient inputs to the AI algorithm.
목차
Abstract
I. 서론
II. 공간 구배값 추정
III. 구배값 추정 실험
IV. 인공지능 구현을 위한 신경망 설계 및 성능 검증
V. 환경 인지 및 위치 추정 응용
VI. 결론
REFERENCES
참고문헌 (15)
참고문헌 신청
K Jo and M. Sunwoo, “Development of localization and mapping software for autonomous cars,” IET Intelligent Transport Systems, vol. 13, no. 2, pp. 406-416, 2019.
J. Sundram, D. Nguyen, G. S. Soh, R. Bouffanais, and K. Wood, “Development of a miniature robot for multi-robot occupancy grid mapping,” 2018 3rd International Conference on Advanced Robotics and Mechatronics (ICARM), pp. 414-419, 2018.
M. Zaffar, S. Ehsan, R. Stolkin, and K. Maier, “Sensors, SLAM and Long-term autonomy: A review”, 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), pp. 285-290, 2018.
A. R. Khairuddin, M. S. Talib, and H. Haron, “Review on simultaneous localization and mapping (SLAM),” 2015 IEEE International Conference on Control System, Computing and Engineering, pp. 85-90, 2015.
L. Qu and H. Wang, “An overview of Robot SLAM problem,” 2011 International Conference on Consumer Electronics, Communications and Networks, pp. 1953-1956, 2011.
J. Sundram, D. Nguyen, G. S. Soh, R. Bouffanais, and K. Wood, “Development of a miniature robot for multi-robot occupancy grid mapping,” 2018 3rd International Conference on Advanced Robotics and Mechatronics (ICARM), pp. 414-419, 2018.
M. Zaffar, S. Ehsan, R. Stolkin, and K. Maier, “Sensors, SLAM and Long-term autonomy: A review”, 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), pp. 285-290, 2018.
A. R. Khairuddin, M. S. Talib, and H. Haron, “Review on simultaneous localization and mapping (SLAM),” 2015 IEEE International Conference on Control System, Computing and Engineering, pp. 85-90, 2015.
L. Qu and H. Wang, “An overview of Robot SLAM problem,” 2011 International Conference on Consumer Electronics, Communications and Networks, pp. 1953-1956, 2011.
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UCI(KEPA) : I410-ECN-0101-2019-003-000760490