To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathem...To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization (ACO) algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm (GA) for dynamic obstacle avoidance in real time.展开更多
With the scale extending of mining, the landslide disaster in the earth’s surface will become more and more serious, and these landslide disasters are being threatened to the sustainable safe mining of the undergroun...With the scale extending of mining, the landslide disaster in the earth’s surface will become more and more serious, and these landslide disasters are being threatened to the sustainable safe mining of the underground mine and the open-pit mine. Based on the theory that sliding force is greater than the shear resistance (resisting force) at the potential slip surface is the necessary and sufficient condition to occur the landslide as the sliding criterion, the principle and method for sliding force remote monitoring is presented, and the functional relationship between the human mechanical quantity and the natural sliding force is derived, hereby, the natural sliding force can be calculated according to the human mechanical quantity. Based on above principle and method, a new system of landslide remote monitoring is designed and 53 systems are installed on the landslide body in the Luoshan mining area, which make up the landslide remote monitoring network. According to the results of field test around 8 months, monitoring curves between sliding force and time are obtained, which can describe and forecast the develop trend of landslide. According to above analysis, the results show that this system has some following advantages: (1) real-time monitoring; (2) remote intelligent transmission; (3) landslides early warning.展开更多
基金Project(60475035) supported by the National Natural Science Foundation of China
文摘To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization (ACO) algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm (GA) for dynamic obstacle avoidance in real time.
基金Project 2006CB202200 supported by the National Basic Research Program of China
文摘With the scale extending of mining, the landslide disaster in the earth’s surface will become more and more serious, and these landslide disasters are being threatened to the sustainable safe mining of the underground mine and the open-pit mine. Based on the theory that sliding force is greater than the shear resistance (resisting force) at the potential slip surface is the necessary and sufficient condition to occur the landslide as the sliding criterion, the principle and method for sliding force remote monitoring is presented, and the functional relationship between the human mechanical quantity and the natural sliding force is derived, hereby, the natural sliding force can be calculated according to the human mechanical quantity. Based on above principle and method, a new system of landslide remote monitoring is designed and 53 systems are installed on the landslide body in the Luoshan mining area, which make up the landslide remote monitoring network. According to the results of field test around 8 months, monitoring curves between sliding force and time are obtained, which can describe and forecast the develop trend of landslide. According to above analysis, the results show that this system has some following advantages: (1) real-time monitoring; (2) remote intelligent transmission; (3) landslides early warning.
