Navigation of unmanned vehicles for civil applications within confined spaces

无人地面车辆(UGV)曾被用于自然、恐怖和意外任务，有时取得了成功，但更多的时候只是确认了它们的潜力。加拿大皇家骑警、加拿大搜救(SAR)和军方已经考虑使用UGV进行行动。UGV在911事件中做得很好，但没有取得巨大的成功，因为机器人无法在倒塌的建筑内执行任务。UGV在已知的地形上表现出了相对的成功，但由于许多原因，它们没有真正的成功，但主要是因为它们无法在未知的复杂、障碍性的室内和室外城市环境中移动，以及无法有效地操纵2.5维和3D地形。在以前工作的基础上，我们将开发目前还没有的导航工具，这些工具与现有工具相结合，将使UGV能够在SAR、侦察和城市治安领域执行任务，使UGV能够在有限的空间内高速自主移动。目标应用专注于旨在支持民防机构、消防队、EMS等的关键行动。我们的目标是两个科学领域：导航和控制。这项工作将集中在行为、目标和战略选择以及探索机制上，这些机制将在搜救、警察和监控场景中进行测试。导航区最初将重点放在2D和3D导航运动上。未来五年的阶段包括：i)为在受限的3D空间工作的UGV开发导航系统；ii)为在未知的2.5维和3D地形中导航的高速UGV开发地形评估方法；以及iii)考虑到机器人的能力和地形条件，将步骤(I)和(Ii)合并到一个新的工具中。STEP(I)将根据机器人的距离/视觉信息及其运动/重构能力开发机器人运动工具。3D地形地图将被用来开发一个动态配置空间，机器人将从那里确定克服地形条件的运动。步骤(Ii)将开发一种计算成本低的机制，以根据UGV的参数和地形轮廓/特征的变化来估计UGV的速度和转角。

Unmanned Ground Vehicles (UGVs) have been used in natural, terrorists and accidental missions sometimes with success, but more often just confirming their potential. The RCMP, Canada Search & Rescue (SAR) and the military have considered using UGVs for their operations. UGVs did well, during the 9/11 incident but without a huge success as the robots couldn't perform tasks within the collapsed buildings. UGVs have shown relative success in known terrains but no real success otherwise due to a number of reasons but mainly due to their inability to move within unknown complex obstructed indoor and outdoor urban environments and effectively maneuver 2½D & 3D terrains. Based on previous work we will develop navigational tools not available today that when coupled with existing tools will enable UGVs execute missions in the areas of SAR, reconnaissance and urban policing enabling UGVs move autonomously within confined spaces at high speeds. The target applications focus on critical operations aimed at supporting civil protection agencies, fire brigades, EMS, etc. We target two scientific areas: navigation and control. The work will focus on behaviors, goal & strategy selection, and exploration mechanisms that will be tested on SAR, police and surveillance scenarios. The navigation area will initially focus on 2½D and 3D navigation motion. The phases for the next five years include: i) Develop a navigation system for UGVs working in confined 3D spaces; ii) Develop a terrain assessment method for high speed UGVs navigating in unknown 2½D & 3D terrains; and iii) Merge Steps (i) and (ii) into a novel tool taking into consideration the robot's capabilities and the terrain conditions. Step (i) will develop robot motion tools based on the robot's range / visual information and its motion / reconfiguration capabilities. A 3D map of the terrain will be used to develop a dynamic configuration space from where the robot will determine the motions to overcome the terrain conditions. Step (ii) will develop a computationally inexpensive mechanism to estimate the velocity and turn angle of the UGV based on the UGV's parameters and changes in the terrain profile/characteristics.