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This paper proposes an obstacle detection method using reflective intensity of the Laser Imaging Detection and Ranging (LIDAR) in close range for the brush cutter. So far, the authors proposed a brush cutting robot equipped with commercially available brush cutter and verified its autonomous mowing capability. In order to safely operate a brush-cutting robot, stone obstacles on the vegetation around the brush cutter should be detected and avoided. The 3D-LIDAR consisting of a combination of the 2D-LIDAR and tilting mechanism is used to collect the environmental information around the brush cutter. This study attempts to identify stone obstacles on the grass using reflective intensity of the 3D-LIDAR. Correction formula of the LIDAR intensity of the grass is developed for the influence of wetness and ambient light. Outdoor experiments under different weather conditions resulted in successful detection of stone objects in the grass field. : Brush-cutting robot, LIDAR, Reflective intensity, Autonomous mobile robot 1. 緒 言 日本国において,少子高齢化に伴い農業分野における就労人口も減少が続いている.また,農作業は他業種に 比べて機械化が難しく人の手による負荷が高く,刃物を用いる危険な作業を伴うことが多い.このような背景か ら農作業の労働環境を改善し,負担を軽減する技術開発が求められている.日本国農林水産省は,「農作業の軽労 化に向けた農業自動化・アシストシステムの開発」(農林水産省,2014)として危険な就労環境を改善し,新規参 入者の円滑な営農等に対処するための研究を行っている.なかでも,頻度が多く負荷の高い農作業の一つに,除 草作業が挙げられる.除草作業の機械化・自動化に関する分野の研究開発では,乗用型草刈機の自動化(富士重 工業, )や,畦畔除草ロボット(中土他,2012)の研究が進められている.しかし,これらのロボットの除 草対象は,メヒシバやセイタカアワダチソウ等の大型雑草ではなく背の低いシバを対象としている.一方,作業 対象となる所が不整地で草の丈が長い場所での刈払作業は,背負式や桿式の刈払機を用いて人力によって行われ ている. この様な環境で人間に代わって自動的に刈払作業を行うことができるロボットを開発することが出来れ 刈払ロボットのための LIDAR の受光強度情報を用いた 植生に含まれる石質障害物の検出手法 Stone obstacle detection method on the vegetation with LIDAR intensity of the ground surface for brush cutting robot *1 National Defense Academy. Graduate School of Science and Engineering, Electronics and Information Engineering, 1-10-20 Hashirimizu, Yokosuka-shi, Kanagawa 239-8686, Japan *2 National Defense Academy. Dept. of Computer Science 1-10-20 Hashirimizu, Yokosuka-shi, Kanagawa 239-8686, Japan Received 27 February 2014

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Stone obstacle detection method on the vegetation with LIDAR intensity of the ground surface for brush cutting robot (Proposition of correction formula for LIDAR intensity under the influence of wetness and ambient light)