Abstract-For many applications in Urban Search and Rescue (USAR) scenarios robots need to learn a map of unknown environments. We present a system for fast online learning of occupancy grid maps requiring low computational resources. It combines a robust scan matching approach using a LIDAR system with a 3D attitude estimation system based on inertial sensing. By using a fast approximation of map gradients and a multi-resolution grid, reliable localization and mapping capabilities in a variety of challenging environments are realized. Multiple datasets showing the applicability in an embedded handheld mapping system are provided. We show that the system is sufficiently accurate as to not require explicit loop closing techniques in the considered scenarios. The software is available as an open source package for ROS.

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Abstract. Key abilities for robots deployed in urban search and rescue tasks include autonomous exploration of disaster sites and recognition of victims and other objects of interest. In this paper, we present related open source software modules for the development of such complex capabilities which include hector slam for self-localization and mapping in a degraded urban environment. All modules have been successfully applied and tested originally in the RoboCup Rescue competition. Up to now they have already been re-used and adopted by numerous international research groups for a wide variety of tasks. Recently, they have also become part of the basis of a broader initiative for key open source software modules for urban search and rescue robots.

Abstract-Finding injured humans is one of the primary goals of any search and rescue operation. The aim of this paper is to address the task of automatically finding people lying on the ground in images taken from the on-board camera of an unmanned aerial vehicle (UAV).In this paper we evaluate various state-of-the-art visual people detection methods in the context of vision based victim detection from an UAV. The top performing approaches in this comparison are those that rely on flexible part-based representations and discriminatively trained part detectors. We discuss their strengths and weaknesses and demonstrate that by combining multiple models we can increase the reliability of the system. We also demonstrate that the detection performance can be substantially improved by integrating the height and pitch information provided by on-board sensors. Jointly these improvements allow us to significantly boost the detection performance over the current de-facto standard, which provides a substantial step towards making autonomous victim detection for UAVs practical.

Team ViGIR entered the 2013 DARPA Robotics Challenge (DRC) with a focus on developing software to enable an operator to guide a humanoid robot through the series of challenge tasks emulating disaster response scenarios. The overarching philosophy was to make our operators full team members and not just mere supervisors. We designed our operator control station (OCS) to allow multiple operators to request and share information as needed to maintain situational awareness under bandwidth constraints, while directing the robot to perform tasks with most planning and control taking place onboard the robot. Given the limited development time, we leveraged a number of open source libraries in both our onboard software and our OCS design; this included significant use of the robot operating system libraries and toolchain. This paper describes the high level approach, including the OCS design and major onboard components, and it presents our DRC Trials results. The paper concludes with a number of lessons learned that are being applied to the final phase of the competition and are useful for related projects as well. C 2014 Wiley Periodicals, Inc. Kohlbrecher et al.: Human-Robot Teaming for Rescue Missions • 353independence (Huang et al., 2007). The human members of the team function as supervisors who set high-level goals, teammates who assist the robot with perception tasks, and operators who directly change robot parameters to improve performance (Scholtz, 2003); as these roles change dynamically during a set task in our system, we will use the term operator generically. Following Bruemmer et al. (2002), we rarely operate in teleoperation where we directly control a joint value, and we primarily operate in shared mode where the operator specifies tasks or goal points. In shared mode, the robot plans its motions to avoid obstacles and then executes the motion only when given permission. Even when executing a footstep plan in autonomous mode, the operator still has supervisory control of the robot and can command the robot to stop walking at any time and safely revert to a standing posture.Team ViGIR entered the DRC as a "Track B" team competing in the DARPA Virtual Robotics Challenge (VRC). Initially, Team ViGIR was composed of TORC Robotics, 2 the Simulation, Systems Optimization, and Robotics Group at Technische Universität Darmstadt (TUD), 3 and the 3D Interaction Group at Virginia Tech. 4 With only eight months from program kickoff to the first competition, the team focused on providing basic robot capabilities needed for the three tasks in the VRC. A short overview of our VRC approach is available in Kohlbrecher et al. (2013).While the tasks and requirements for the VRC were based on those anticipated in a real scenario, there were important differences: sensor noise was low and more predictable, simple friction models were used, there was no need for calibrating sensors or joint angle offsets for the robot, and the environments were known ahead of time. The dynamic model used for simulating the Atlas robot was ava...

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