Multi-Sensor Fusion Based on BPNN in Quadruped Ground Classification
文献类型：会议论文
| 作者 | Huang Zhuhui1,2 ; Wang Wei1
|
| 出版日期 | 2017 |
| 会议日期 | 2017 |
| 会议地点 | Takamatsu, Japan |
| 关键词 | Trajectory Planning Quadruped Robot Terrain Classification Bpnn Multi-sensor Fusion |
| 页码 | 1620-1625 |
| 英文摘要 | Appropriate perception of different ground substrates plays an essential role in realizing adaptive quadruped locomotion. In this paper, we propose a multi-sensor fusion method based on Back Propagation Neural Network (BPNN) using in real-time ground substrate classification for adaptive quadruped walking. In order to collect the body gyro information, foot-ground contact force, Direct Current (DC) motor information and joint angle to train the network, we present the enhanced walk strategy with Center of Gravity (COG) adjustment method with 6-axis motion sensor feedback and realize steady walk gait on different ground substrates. Using these method, the quadruped robot Biodog realizes multi-sensor information collection while walking on six different ground substrates. Then we train the BPNN using the collected data after calculation and normalization. In network training, about 99.83% samples have been classified correctly using BPNN. In real-time testing, about 98.33% has been classified successfully using trained BPNN. |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/20932]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2.University of Chinese Academy of Sciences, 19 A Yuquan Rd, Shijingshan District, Beijing 100049, China |
| 推荐引用方式 GB/T 7714 | Huang Zhuhui,Wang Wei. Multi-Sensor Fusion Based on BPNN in Quadruped Ground Classification[C]. 见:. Takamatsu, Japan. 2017. |
入库方式： OAI收割
来源：自动化研究所
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