行動式機器人排隊模式

Abstract

機器人不只是實驗室的研究議題或工廠中的生產工具，也是人類生活中的一分子。排隊是人類生活中常見的社交行為之一，為了達到人類和機器人共存的社會，排隊是機器人一個重要的模式。機器人裝備攝影機和雷射測距儀，利用同步定位、建地圖和移動物體追縱(SLAMMOT)和人類偵測(human detection)，機器人能對環境做初步的了解。 我們提出三種排隊的模式，不可見限制下的排隊模式，部分可見限制下的排隊模式和在沒有限制環境下的排隊模式。利用曲線擬合(curve fitting)，將外插值當作下個隊伍位子的預測，同時考慮個人空間、障礙物避免、隊伍形狀。在部分可見限制環境下，感測器難以偵測出所有限制，可藉由人類的行為了解其限制，並表現出人類可接受的行為。在沒有限制環境下，機器人參考人類的位置，形成一個線性規劃的問題，得到一個合適的地點做為等待依據，最後採用社會導航(social navigation)方式到達目的地。

Robots are studied not only for their uses in laboratories and factories, but with an eye to incorporating them into human daily life. One of the commonest human social behaviors involves becoming a member of a queue, so for robots to integrate and co-exist with humans, queuing is an important skill to acquire. Given a camera and laser rangefinder, the robot will be able to map its environment, and it can then use Simultaneous Localization and Mapping, together with Moving Object Tracking (SLAMMOT), and a human detection algorithm to provide itself with a preliminary understanding of that environment. Three categories of queuing model are proposed: with visible and invisible constraints, with partially visible constraints, and with no constraints within the environment. To decide the position to take relative to the rest of the queue, the algorithm uses curve fitting to perform the extrapolation, and takes into account invisible constraints such as personal space, as well as visible ones like obstacles and the direction of the queue. Where there are partial visible constraints, like stretch barriers, human behavior provides a cue to identify constraints that are hard for sensors to detect. The robot needs to observe what the humans are doing so that it can understand the constraints and behave in a way acceptable to the surrounding people. In an unconstrained environment, the robot can use the positions of human queue members as a reference, solving a linear programming problem to decide where to stand and the socially acceptable way to move toward it.