文献一覧: 森岡一幸 (著者)

1 0 0 0 OA 知能化空間における移動ロボットの人間追従制御

著者: 森岡一幸李周浩橋本秀紀
出版者: The Robotics Society of Japan
雑誌: 日本ロボット学会誌 (ISSN:02891824)
巻号頁・発行日: vol.22, no.1, pp.103-111, 2004-01-15 (Released:2010-08-25)
参考文献数: 17
被引用文献数: 5 5

In the environment that human and robots coexist, mobile robots have to approach human as much as possible in order to provide human with physical services. For friendly interaction with human, the robots should be able to afford human-affinitive movement. In this paper, human following, as one of human-affinitive movements, of robot is achieved. The human following robot requires several techniques; the recognition of the target human, the recognition of the environment around the robot, and the control strategy for stable human following. In this research, Intelligent Space, where many sensors and intelligent devices are distributed, is used for the recognition of the target human and the environment around the robot. The control law based on the virtual spring model is proposed to mitigate the difference of movement between the human and the mobile robot. The proposed control law is applied to Intelligent Space and its performance is verified by computer simulation and experiment.

2022-05-18 11:15:03
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1 0 0 0 既存の電子地図からの移動ロボットの行動学習用地図の自動生成

著者: 海保諒森岡一幸
出版者: 一般社団法人日本機械学会
雑誌: ロボティクス・メカトロニクス講演会講演概要集
巻号頁・発行日: vol.2020, pp.2A1-N10, 2020

<p>The paper introduces a method of automatic map generation used for learning of action policy in mobile robot navigation. Road contours and waypoint candidates are extracted as map components by image processing from an image of existing electronic map such as Google Map. Road contours are extracted using topological structural analysis of the binarized electronic map image. Also, waypoint candidates used as respawn or destination points in learning system are randomly selected from pixels of road areas. The generated map can be applied to learning simulator based on deep reinforce learning system. The paper describes an abstract of navigation system based on reinforcement learning, a proposed map generation method.</p>

2021-09-01 05:15:05
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1 0 0 0 フレーム毎にMCと3次元予測を最適化する動画像の可逆符号化方式(<小特集>画像の処理と符号化)

著者: 塩寺太一郎梅津有司前田弘樹松田一朗森岡一幸伊東晋
出版者: 一般社団法人映像情報メディア学会
雑誌: 映像情報メディア学会誌 : 映像情報メディア (ISSN:13426907)
巻号頁・発行日: vol.60, no.7, pp.1051-1058, 2006-07-01
被引用文献数: 13 1

A novel lossless coding scheme for video signals is described. The scheme uses a block-adaptive 3D prediction method that predicts a video signal based on both the current and motion-compensated previous frames. The resulting prediction errors are encoded by using a kind of context-adaptive arithmetic coder. Several coding parameters such as prediction coefficients and motion vectors are iteratively optimized for each frame so that the overall coding rate can be a minimum. Moreover, a quadtree-based variable block-size motion compensation technique is introduced for efficient representation of motion information. Experimental results show that the coding rates of our scheme are 11-17% lower than those of the H. 264-based lossless coding scheme.<p>お詫びと訂正 : 本論文 (pp. 1051~1058) の1052頁と1053頁を入れ違えておりました. ここにお詫びして訂正版を8月号に掲載いたします.