Robots are used for Urban Search and Rescue to assist rescue workers. To enable the robots to find victims, they are equipped with various sensors including thermal, video and depth time-of-flight cameras, and laser range-finders. We present a method to enable a robot to perform this task autonomously. Thermal features are detected using a dynamic temperature threshold. By aligning the thermal and time-of-flight camera images, the thermal features are projected into 3D space. Edge detection on laser data is used to locate holes within the environment, which are then spatially correlated to the thermal features. A decision tree uses the correlated features to direct the autonomous policy to explore the environment and locate victims. The method was evaluated in the 2010 RoboCup Rescue Real Robots Competition.
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机译：机器人用于城市搜索和救援，以协助救援人员。为了使机器人能够找到受害者，他们配备了各种传感器，包括热，视频和深度飞行时间摄像头以及激光测距仪。我们提出了一种使机器人能够自主执行此任务的方法。使用动态温度阈值检测热特征。通过对齐热图像和飞行时间相机图像，热特征将投影到3D空间中。激光数据的边缘检测用于定位环境中的孔，然后将这些孔在空间上与热特征相关联。决策树使用相关功能来指导自治策略来探索环境并找到受害者。该方法在2010年RoboCup Rescue Real Robots竞赛中得到了评估。
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