Socially Aware Mobile Robot Navigation System - An Open-source Software Platform

社会意识的机器人导航系统，使一个移动的机器人自主导航的社会环境，如机场，商场，博物馆是高度期望部署移动的机器人为我们的日常服务。第一个也是最重要的问题，让一个移动的机器人在社会环境中工作的是，机器人必须避免不仅是经常性的障碍，但也是人类，同时安全和社会导航向一个给定的goal.We将调查和开发一个社会意识的机器人导航系统，将社会时空特征的人类社会反应的运动模型。在这个项目中，我们将开发一个社会反应运动模型（SRM）添加到传统的机器人导航方案，使移动的机器人，以处理不同的社会情况下，个人和人类群体在社会环境中导航。SRM由四个功能模块组成：（1）人体检测与跟踪，即检测并跟踪机器人附近的人体;（2）人体状态提取，即提取人体的位置、方向、速度和姿态;（3）人体群体估计，即估计交互人体的群体;（4）社会反应控制将个人和人类群体的信息纳入扩展的社会力模型。SRM可以集成在传统的路径规划上，例如D*，RRT，以生成社交感知的机器人运动规划，该规划使机器人能够朝着给定的目标导航，同时社交地和反应性地避开个人，人类群体，其他机器人和环境障碍物。具有社会意识的机器人导航系统将在基于ROS的软件平台上开发，该平台将在Quanser提供的QBot 2上进行集成和测试。

A socially aware robot navigation systems that enables a mobile robot to autonomously navigate in social environments such as airports, shopping malls, museums is highly expected to deploy mobile robots for our daily services. The first and most important issue to allow a mobile robot to work in a social environment is that the robot must avoid not only regular obstacles but also humans while navigating safely and socially towards a given goal.We will investigate and develop a socially aware robot navigation system by incorporating socio-spatio-temporal characteristics of humans on a social reactive motion model. In this project, we will develop a social reactive motion model (SRM) added on the conventional robot navigation scheme to enable the mobile robot to deal with different social situations of individuals and human groups when navigating in social environments. SRM is composed of four functional blocks: (1) human detection and tracking is to detect and track humans in the vicinity of the robot; (2) human state extraction is to extract human position, orientation, velocity and human postures; (3) human group estimation is to estimate groups of interactive humans; (4) social reactive control incorporates information of individuals and human groups into an extended social force model. SRM can be integrated on a conventional path planning, e.g. D*, RRT, to generate a socially aware robot motion planning that enables the robot to navigate towards the given goal while socially and reactively avoiding individuals, human group, other robots, and environmental obstacles. The socially aware robot navigation system will be developed on a ROS-based software platform that will be integrated and tested on QBot2 provided by Quanser.