全区域覆盖移动机器人无标识工作环境的边界建立与识别

针对工作在户外环境中的全区域覆盖移动机器人，提出在无人为标识的工作环境中,建立边界和识别边界的新方案. 设计组合传感器定位系统实现工作区域的边界建立和识别. 基于分段策略建立工作边界地图，并对其性能与连续获取策略进行比较分析. 设计RBF神经网络以实时获取精确的定位信息. 实验证明， 定位系统和方案能够保证工作区域边界的准确建立和成功识别，机器人能顺利完成全区域覆盖任务，而且具有一定的工程实用性.

Establishment and Identification of Unmarked Operational Environment Boundary for Area-covering Mobile Robots

According to the specialties of the area-covering mobile robots working in the outdoor environment, a new solution to the boundary set-up and identification of unmarked operational area is proposed. The designed localization system with combined sensors serves robots reliably to establish and identify boundaries of the operational area. Boundary map is established based on the subsection acquisition strategy, and its performance is analyzed and compared with the continuous acquisition strategy. The RBF neural network is designed for mobile robots to acquire the accurate and real-time localization information. The results of experiment show that the localization system and the solution can guarantee the successful establishment and identification of operational area boundary, mobile robots with the engineering practicability can complete the task of covering every part of the operational area.