Stefan Kohlbrecher

Learn More
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(More)
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(More)
Quadrotor UAVs have successfully been used both in research and for commercial applications in recent years and there has been significant progress in the design of robust control software and hardware. Nevertheless, testing of prototype UAV systems still means risk of damage due to failures. Motivated by this, a system for the comprehensive simulation of(More)
Stefan Kohlbrecher, Alberto Romay, Alexander Stumpf, Anant Gupta, and Oskar von Stryk Simulation, Systems Optimization and Robotics Group, CS Dept. Technische Universität Darmstadt, Hochschulstrasse 10, 64289, Darmstadt, Hesse, Germany e-mail: kohlbrecher@sim.tu-darmstadt.de, romay@sim.tu-darmstadt.de, stumpf@sim.tu-darmstadt.de, gupta@sim.tu-darmstadt.de,(More)
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(More)
In urban search and rescue scenarios, typical applications of robots include autonomous exploration of possibly dangerous sites, and the recognition of victims and other objects of interest. In complex scenarios, relying on only one type of sensor is often misleading, while using complementary sensors frequently helps improving the performance. To that end,(More)
In recent years, the numbers of life-size humanoids as well as their mobility capabilities have steadily grown. Stable walking motion and control for humanoid robots are already well investigated research topics. This raises the question how navigation problems in complex and unstructured environments can be solved utilizing a given black box walking(More)
Motivated by the DARPA Robotics Challenge (DRC), the application of operator assisted (semi-)autonomous robots with highly complex locomotion and manipulation abilities is considered for solving complex tasks in potentially unknown and unstructured environments. Because of the limited a priori knowledge about the state of the environment and tasks needed to(More)
Humanoid robotic manipulation in unstructured environments is a challenging problem. Limited perception, communications and environmental constraints present challenges that prevent fully autonomous or purely teleoperated robots from reliably interacting with their environment. In order to achieve higher reliability in manipulation we present an approach(More)