• 제목/요약/키워드: DVGM(Directional Velocity Grid Map)

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무인차량의 주행성분석을 위한 방향별 속도지도 생성 (The Generation of Directional Velocity Grid Map for Traversability Analysis of Unmanned Ground Vehicle)

  • 이영일;이호주;지태영
    • 한국군사과학기술학회지
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    • 제12권5호
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    • pp.549-556
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    • 2009
  • One of the basic technology for implementing the autonomy of UGV(Unmanned Ground Vehicle) is a path planning algorithm using obstacle and raw terrain information which are gathered from perception sensors such as stereo camera and laser scanner. In this paper, we propose a generation method of DVGM(Directional Velocity Grid Map) which have traverse speed of UGV for the five heading directions except the rear one. The fuzzy system is designed to generate a resonable traveling speed for DVGM from current patch to the next one by using terrain slope, roughness and obstacle information extracted from raw world model data. A simulation is conducted with world model data sampled from real terrain so as to verify the performance of proposed fuzzy inference system.

Modified $A^*$ - 방향별 속도지도를 활용한 무인차량의 지역경로계획 (Modified $A^*$ - Local Path Planning Method using Directional Velocity Grid Map for Unmanned Ground Vehicle)

  • 이영일;이호주;박용운
    • 한국군사과학기술학회지
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    • 제14권3호
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    • pp.327-334
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    • 2011
  • It is necessary that UGV(Unmanned Ground Vehicle) should generate a real-time travesability index map by analyzing raw terrain information to travel autonomously tough terrain which has various slope and roughness values. In this paper, we propose a local path planning method, $MA^*$(Modified $A^*$) algorithm, using DVGM (Directional Velocity Grid Map) for unmanned ground vehicle. We also present a path optimization algorithm and a path smoothing algorithm which regenerate a pre-planned local path by $MA^*$ algorithm into the reasonable local path considering the mobility of UGV. Field test is conducted with UGV in order to verify the performance of local path planning method using DVGM. The local path planned by $MA^*$ is compared with the result of $A^*$ to verify the safety and optimality of proposed algorithm.