Research in Nepal

Findings from University of Dayton geologist, Umesh Haritashya, after the deadly earthquake in Nepal April 25 will be published in a forthcoming article in Science, the leading journal on original scientific research

A Holistic Approach for Highly Versatile Supervised Autonomous Urban Search and Rescue Robots

The use of robots for search and rescue tasks has tremendous potential to mitigate disasters and save lives of both of disaster victims and first responders. Moreover, robots actually deployed for disaster response are neither highly intelligent (i.e. autonomous) nor do they intelligently make best use of a human supervisor in the loop nor do multiple heterogeneous robots work together in an intelligent manner. Within this thesis, a holistic systems-oriented approach together with a number of developments of key functionalities to increase robot autonomy for rescue robots systems are presented and evaluated. These are usable for a wide range of robotic systems and operation modes, from unmanned ground vehicles for exploration and surveillance to complex high degree of freedom humanoid robotic systems that can be used for remote manipulation in disaster environments and thus, may potentially serve as "avatars" for human response forces supervising them. Importantly, cooperation between one or more human supervisors and such robotic systems is demonstrated, increasing overall reliability and capability. The presented approaches are evaluated in simulated and real world robot experiments and presented within the scope of some of the most competitive international competitions for rescue and disaster response robots in the world, the the DARPA Robotics Challenge competition and the RoboCup Rescue Robot League, demonstrating their performance beyond laboratory environments and representing an important milestone towards their future use in real disaster environments

A Holistic Approach for Highly Versatile Supervised Autonomous Urban Search and Rescue Robots

The use of robots for search and rescue tasks has tremendous potential to mitigate disasters and save lives of both of disaster victims and first responders. Moreover, robots actually deployed for disaster response are neither highly intelligent (i.e. autonomous) nor do they intelligently make best use of a human supervisor in the loop nor do multiple heterogeneous robots work together in an intelligent manner. Within this thesis, a holistic systems-oriented approach together with a number of developments of key functionalities to increase robot autonomy for rescue robots systems are presented and evaluated. These are usable for a wide range of robotic systems and operation modes, from unmanned ground vehicles for exploration and surveillance to complex high degree of freedom humanoid robotic systems that can be used for remote manipulation in disaster environments and thus, may potentially serve as "avatars" for human response forces supervising them. Importantly, cooperation between one or more human supervisors and such robotic systems is demonstrated, increasing overall reliability and capability. The presented approaches are evaluated in simulated and real world robot experiments and presented within the scope of some of the most competitive international competitions for rescue and disaster response robots in the world, the the DARPA Robotics Challenge competition and the RoboCup Rescue Robot League, demonstrating their performance beyond laboratory environments and representing an important milestone towards their future use in real disaster environments

3D Point Cloud - Altes Hauptgebäude, TU Darmstadt

3D Point Cloud of the old main building at TU Darmstadt (S1|03, Hochschulstr. 1, 64289 Darmstadt, Germany). The raw data was captured with the Hector Tracker robot (http://www.teamhector.de/our-robot/51-hector-tracker) and processed using the Simultaneous Localization and Mapping approach developed by Kevin Daun based on Google Cartographer. The data set contains 186,896,629 points and the bounding box has a size of 220.2 m x 227.3 m 40.7 m

From RoboCup Rescue to supervised autonomous mobile robots for remote inspection of industrial plants

With increasing capabilities and reliability of autonomous mobile robots, inspection of remote industrial plants in challenging environments becomes feasible. With the ARGOS challenge, oil and gas company TOTAL S.A. initiated an international competition aimed at the development of the first autonomous mobile robot which can safely operate in complete or supervised autonomy over the entire onshore or offshore production site, potentially in hazardous explosive atmospheres and harsh conditions. In this work, the approach of joint Austrian–German Team ARGONAUTS towards solving this challenge is introduced, focussing on autonomous capabilities. These build on functional components developed during prior participation in the RoboCup Rescue Robot League

Optimization-Based Planning for Autonomous Traversal of Obstacles with Mobile Ground Robots

Mobile robotic platforms which are traversing unstructured environments with challenging uneven terrain are permanently endangered of falling over. Previous research on trajectory planning methods for the prevention of vehicle tip-over is mostly limited to basic mobility systems with only few degrees of freedom (DOF). This paper proposes a novel optimization-based planning approach that enables mobile robots to autonomously traverse obstacles and rough terrain more safely. A 3D world model as provided from external sensors like Lidar is used to compute a whole-body motion plan in advance by optimizing the trajectories of each joint. Active flipper tracks maximize ground contact for improved traction and, if available, manipulator arm joints are used to further improve stability metrics. Additional constraints prevent collisions with the environment and the robot itself. The presented approach makes only few assumptions about the robot’s configuration and is applicable to a wide range of wheeled or tracked platforms. This is demonstrated by experimental evaluation for two different robots in simulation and for one physical robot. In four different test scenarios it is shown, that the proposed approach effectively prevents vehicle tip-over during traversal of uneven ground