利用動態環境航行感知預測以建構排隊模型

為了要使得機器人更容易被人們所接受，機器人必須理解環境中的人類行為。在不久的將來，機器人將頻繁出現在人類生活環境中，像是學校、醫院、辦公大樓、博物館、以及一般家庭等等區域，因此動態環境評估預測變得很重要。而排隊為人類社會最常見的行為之一，所以機器人必須學習相關的知識。個人化服務型機器人是人類社會的下個趨勢，機器人為了能提供擁有者更便利舒適的生活，在到達服飾店門口時，會下載服飾店所提供的衣物3D模型，並可供主人快速試穿的演算法。此外，幫助主人跑腿、買東西、付賬等更是基本功能，因此機器人能夠了解人與人群之間相互關係的排隊行為是急需探討的議題。此篇論文，提出了利用機率來分析動態環境行人排隊的模型，供機器人使用與人類相似的行為模型。更提出了偵測及檢測行人是否進入隊伍的演算法。排進隊伍時如何只用相機做出追蹤前方顧客及做出行動的方法。

關鍵字

排隊；虛擬試穿系統；排隊檢測；動態環境航行；社會行為預測；追蹤

並列摘要

Robots need to understand the human social behaviors to interact with human correctly and to service for people in public and home environments. The way in which robots are going to live with humans has become an important issue. Therefore, estimation and prediction of dynamic human society environment are very important for robot. Standing in line is one of the most common human social behaviors and robot needs to learn it. The imminent trend for our society would be personalization of robots capable of offering services that cater to individual needs. In order to provide a more convenient way of life, the robots are able to download the 3-Dimensional models supplied by the respective apparel stores upon arrival at the entrance. In addition, codes are immediately processed so that their owners could fit the clothes efficiently. Furthermore, apart from their basic functions of replacing their owners in errands such as purchasing goods and paying the bill, they understand the importance of human interactions during the process of queuing. This paper includes the use of probability in analyzing the model of queuing under a dynamic environment. Other than that, this paper also offered formulas in detecting and predicting the situation of queues. Nevertheless, methods of using only cameras to capture and track the customer in front and react to difference of image are also part of the paper.

並列關鍵字

Queuing ； Virtual Fitting Room ； Pedestrian Queuing Detection ； Dynamic Environment Navigation ； Society Behavior Prediction ； tracking

參考文獻

[3] P. Biber, H. Andreasson, T. Duckett, and A. Schilling, "3d Modeling of Indoor Environments by a Mobile Robot with a Laser Scanner and Panoramic Camera," Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, Vol. 4, pp. 3430-3435, 2004.

[4] S.S. Blackman, "Multiple Hypothesis Tracking for Multiple Target Tracking," IEEE Aerospace and Electronic Systems Magazine, Vol. 19, No. 1, pp. 5-18, 2004.

[5] M. Bosse and R. Zlot, "Map Matching and Data Association for Large-Scale Two-Dimensional Laser Scan-Based Slam," International Journal of Robotics Research, Vol. 27, No. 6, pp. 667-691, 2008.

[7] H.T. Cheng, "Algorithms for Partially Observable Markov Decision Processes", Doctoral Dissertation, University of British Columbia, 1988.

[8] M.Y. Cheng, M.C. Tsai, and C.Y. Sun, "Dynamic Visual Tracking Based on Multiple Feature Matching and G–H Filter," Advanced Robotics, Vol. 20, No. 12, pp. 1401-1423, 2006.

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利用動態環境航行感知預測以建構排隊模型

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