In this study,MAPGIS software was used in production of basic farmland protection plan maps based on the related practice of Jinkong town,Yanting County,Sichuan Province,China.It was proved that MAPGIS software could ...In this study,MAPGIS software was used in production of basic farmland protection plan maps based on the related practice of Jinkong town,Yanting County,Sichuan Province,China.It was proved that MAPGIS software could improve the efficiency of mapping greatly,and resolved technical problems in basic farmland protection plan mapping.展开更多
Obstacle avoidance is quite an important issue in the field of legged robotic applications, such as rescuing and detecting in complicated environment. Most related researchers focused on the legged robot’s gait gener...Obstacle avoidance is quite an important issue in the field of legged robotic applications, such as rescuing and detecting in complicated environment. Most related researchers focused on the legged robot’s gait generation after ssuming that obstacles have been detected and the walking path has been given. In this paper we propose and validate a novel obstacle avoidance framework for a six-legged walking robot Hexapod-III in unknown environment. Throughout the paper we highlight three themes: (1) The terrain map modeling and the obstacle detection; (2) the obstacle avoidance path planning method; (3) motion planning for the legged robot. Concretely, a novel geometric feature grid map (GFGM) is proposed to describe the terrain. Based on the GFGM, the obstacle detection algorithm is presented. Then the concepts of virtual obstacles and safe conversion pose are introduced. Virtual obstacles restrict the robot to walk on the detection terrain. A safe path based on Bezier curves, passing through safe conversion poses, is obtained by minimizing a penalty function taking into account the path length subjected to obstacle avoidance. Thirdly, motion planning for the legged robot to walk along the generated path is discussed in detail. At last, we apply the proposed framework to the Hexapod-III robot. The experimental result shows that our methodology allows the robot to walk safely without encountering with any obstacles in unknown environment.展开更多
基金Supported by NSFC(30900138)Open Research Fund of Re-earch Center of Forestry Remote Sensing and Information Engineering,Central South University of Forestry and Technology(RS2008k01)Henan University of Science and Technology Doctor Foundation(09001367)~~
文摘In this study,MAPGIS software was used in production of basic farmland protection plan maps based on the related practice of Jinkong town,Yanting County,Sichuan Province,China.It was proved that MAPGIS software could improve the efficiency of mapping greatly,and resolved technical problems in basic farmland protection plan mapping.
基金supported by the National Basic Research Program of China (Grant No. 2013CB035501)
文摘Obstacle avoidance is quite an important issue in the field of legged robotic applications, such as rescuing and detecting in complicated environment. Most related researchers focused on the legged robot’s gait generation after ssuming that obstacles have been detected and the walking path has been given. In this paper we propose and validate a novel obstacle avoidance framework for a six-legged walking robot Hexapod-III in unknown environment. Throughout the paper we highlight three themes: (1) The terrain map modeling and the obstacle detection; (2) the obstacle avoidance path planning method; (3) motion planning for the legged robot. Concretely, a novel geometric feature grid map (GFGM) is proposed to describe the terrain. Based on the GFGM, the obstacle detection algorithm is presented. Then the concepts of virtual obstacles and safe conversion pose are introduced. Virtual obstacles restrict the robot to walk on the detection terrain. A safe path based on Bezier curves, passing through safe conversion poses, is obtained by minimizing a penalty function taking into account the path length subjected to obstacle avoidance. Thirdly, motion planning for the legged robot to walk along the generated path is discussed in detail. At last, we apply the proposed framework to the Hexapod-III robot. The experimental result shows that our methodology allows the robot to walk safely without encountering with any obstacles in unknown environment.
