Navigation of unmanned vehicles for civil applications within confined spaces

无人地面车辆（ugv）在自然、恐怖和意外任务中使用，有时取得了成功，但更多时候只是证实了它们的潜力。加拿大皇家骑警、加拿大搜救队（SAR）和军方已经考虑使用ugv进行行动。ugv在9/11事件中表现不错，但没有取得巨大成功，因为机器人无法在倒塌的建筑物内执行任务。ugv在已知地形中表现出了相对的成功，但由于许多原因而没有真正的成功，但主要是因为它们无法在未知复杂的室内和室外城市环境中移动，也无法有效地机动2.5 D和3D地形。基于之前的工作，我们将开发目前无法使用的导航工具，当与现有工具相结合时，将使ugv能够在SAR，侦察和城市警务领域执行任务，使ugv能够在有限的空间内以高速自主移动。目标应用侧重于支持民防机构、消防队、EMS等的关键操作。我们的目标是两个科学领域：导航和控制。这项工作将侧重于行为、目标和策略选择以及探索机制，这些机制将在搜救、警察和监视场景中进行测试。导航区域最初将专注于2.5 D和3D导航运动。未来五年的阶段包括：i)为在受限的3D空间中工作的ugv开发导航系统；ii)开发用于高速ugv在未知的2.5 D和3D地形中导航的地形评估方法；考虑到机器人的能力和地形条件，将步骤(i)和（ii）合并为一个新的工具。步骤(i)将基于机器人的距离/视觉信息及其运动/重新配置能力开发机器人运动工具。地形的3D地图将用于开发一个动态配置空间，机器人将从中确定克服地形条件的运动。步骤（ii）将开发一种计算成本低廉的机制，根据UGV的参数和地形剖面/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.