Robotic 3D Visual Mapping for Augmented Situational Awareness in Unstructured Environments

This paper describes our experiences in the application of localization and mapping techniques to aid mobile robots in reaching and exploring terrains which are inaccessible or considered too dangerous for humans. The work is driven, in particular, by the practical constrains to deploy (semi)autonomous platforms in unstructured search and rescue scenarios, where prior knowledge of the environment is unavailable but required before a rescue operation can be dispensed. Smaller, tracked, highly mobile vehicles have been found to be most capable of navigating such challenging environments in six degrees of freedom. Yet they are not able to carry large payloads, such as the ubiquitous SICK laser range scanner, particularly if long-term autonomy is also expected. In this work a mobile robot equipped with a range of sensor packages to best provide useful and understandable information about the interior of a collapsed building in the form of dense 3D maps, which humans can use to navigate and locate victims, is described. The sensorial arrangements employed, and the augmented algorithms adopted to suit the requirements of such challenging field deployment, are also presented. Appearance sensors, capable of providing scene texture information to the rescuer and also provide salient visual features for “place recognition”, feature prominently. In particular, a time-of-flight range imager coupled with a standard high-resolution camera has been used within a delayed-state SLAM formulation in the information form with encouraging results. Tests with monocular and stereoscopic rigs which constitute the initial inspiration of this research work will also be documented. Data collected from a mock-up urban search and rescue arena which simulates a multi-level disaster area has been used to validate the proposed approaches. Despite their limitations, the resulting 3D maps have been found to be effective navigation tools, both for the rescuer as well as for the autonomous platform. Key: Visual 6 DoF SLAM, 3D texture maps, unstructured environments. Motivation: 3D mapping for USAR robotics Urban search and rescue is related to the emergency response dealing with the collapse of man-made structures. With the advances of technology and the increasing numbers of large earthquakes (California 1989, Kobe 1995, Izmit 1999), terrorist attacks (NY 2001), landslides (Cauca 1994) hurricanes (Mitch 1998) and other catastrophes, the need to devote resources in dealing with the aftermath of these natural and human-caused disasters is all but too apparent. Search and rescue is therefore becoming an important application area for mobile robots where the robots are employed with the ultimate objective of helping in identifying and rescuing victims from a hostile environment. In this process, one of the key objectives is to send a robot to explore unstructured terrains which are inaccessible or considered too dangerous for rescue workers, have it navigate in this environment and build a map that could be used by human rescuers to retrieve victims. Robots have also the ability to bring in medical support and supplies to the victims, hence increasing their chances of