| Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion |
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| 作者姓名： | 韩宝玲 张天 罗庆生 朱颖 宋明辉 |
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| 作者单位： | School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China,School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China,School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China,School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China,School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China |
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| 基金项目： | Supported by the Ministerial Level Advanced Research Foundation(40401060305) |
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| 摘 要： | In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4.6.cm, which meets the application requirements of the robot.
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| 关 键 词： | multi-sensor Kalman filter algorithm constant velocity (CV) model STF fusion algorithm obstacle avoidance of robot |
| 收稿时间： | 2014/12/6 0:00:00 |
Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion |
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| HAN Bao-ling,ZHANG Tian,LUO Qing-sheng,ZHU Ying and SONG Ming-hui.Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion[J].Journal of Beijing Institute of Technology,2016,25(4):448-454. |
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| Authors: | HAN Bao-ling ZHANG Tian LUO Qing-sheng ZHU Ying and SONG Ming-hui |
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| Affiliation: | 1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China;2. School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China;3. School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4.6.cm, which meets the application requirements of the robot. |
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| Keywords: | multi-sensor Kalman filter algorithm constant velocity (CV) model STF fusion algorithm obstacle avoidance of robot |
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