Oehler, Martin (2018):
Whole-Body Planning for Obstacle Traversal with Autonomous Mobile Ground Robots.
Darmstadt, Technische Universitaet Darmstadt, Department of Computer Science (SIM), [Master Thesis]

Abstract

Advances in the design of mobile robotics systems enable the application in new tasks like disaster response, inspection and logistics. Recently, autonomous robots have been a major focus of research. Compared to teleoperated machines, they work faster and more efficiently especially in environments with degraded connectivity. Without human supervision, the underlying algorithms need to be robust against unexpected circumstances to prevent damage to the robotic system and the environment. A common challenge for autonomous robots is the traversal of obstacles. To continue its task, the robot has to cross the obstacle without tipover instabilities. So far, research on prevention of vehicle tipover is mostly limited to simple systems with few degrees of freedom (DOF). In this thesis, a novel whole-body motion planning approach is proposed. By using a model of the world, the joint configuration is optimized for stability along a given path. The proposed method evaluates whether a safe traversal is possible and generates a motion plan that allows the robot to cross generic obstacles without tipover. Collisions are prevented by modeling them as constraints of the optimization. This approach is evaluated on a tracked vehicle with adjustable flippers and a five DOF manipulator arm. The proposed method leverages the flippers to improve stability by maximizing ground support and the arm to shift the center of mass. Additionally, the platform features various sensors to perceive its environment. Performance of the whole-body motion planning is evaluated in simulation and on the real robot. In multiple scenarios, it is shown that the approach effectively prevents tipover and increases robot stability.

Item Type:	Master Thesis
Erschienen:	2018
Creators:	Oehler, Martin
Title:	Whole-Body Planning for Obstacle Traversal with Autonomous Mobile Ground Robots
Language:	English
Abstract:	Advances in the design of mobile robotics systems enable the application in new tasks like disaster response, inspection and logistics. Recently, autonomous robots have been a major focus of research. Compared to teleoperated machines, they work faster and more efficiently especially in environments with degraded connectivity. Without human supervision, the underlying algorithms need to be robust against unexpected circumstances to prevent damage to the robotic system and the environment. A common challenge for autonomous robots is the traversal of obstacles. To continue its task, the robot has to cross the obstacle without tipover instabilities. So far, research on prevention of vehicle tipover is mostly limited to simple systems with few degrees of freedom (DOF). In this thesis, a novel whole-body motion planning approach is proposed. By using a model of the world, the joint configuration is optimized for stability along a given path. The proposed method evaluates whether a safe traversal is possible and generates a motion plan that allows the robot to cross generic obstacles without tipover. Collisions are prevented by modeling them as constraints of the optimization. This approach is evaluated on a tracked vehicle with adjustable flippers and a five DOF manipulator arm. The proposed method leverages the flippers to improve stability by maximizing ground support and the arm to shift the center of mass. Additionally, the platform features various sensors to perceive its environment. Performance of the whole-body motion planning is evaluated in simulation and on the real robot. In multiple scenarios, it is shown that the approach effectively prevents tipover and increases robot stability.
Place of Publication:	Darmstadt
Divisions:	20 Department of Computer Science 20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
Date Deposited:	06 Jun 2019 06:06
URL / URN:	https://web.sim.informatik.tu-darmstadt.de/publ/da/2018_Oehl...
PPN:
Referees:	von Stryk, Prof. Dr. Oskar ; Kohlbrecher, Dr.-Ing Stefan
Alternative Abstract:	Alternative abstract Language Fortschritte in der Entwicklung mobiler Robotersysteme ermöglichen den Einsatz in neuen Aufgabengebieten wie Katastrophenschutz, Inspektion und Logistik. Seit K urzem sind autonome Roboter ein Schwerpunkt der Forschung. Im Vergleich zu ferngesteuerten Maschinen arbeiten sie schneller und effizienter, insbesondere in Umgebungen mit eingeschränkter Konnektivität. Ohne menschliche Aufsicht müssen die zugrunde liegenden Algorithmen jedoch robust gegen unerwartete Umstände sein, um Schäden am Robotersystem und der Umwelt zu vermeiden. Eine besondere Herausforderung für autonome Roboter ist die Überwindung von Hindernissen. Um seine Aufgabe fortsetzen zu können, muss der Roboter in der Lage sein, das Hindernis sicher zu überqueren. Bisher beschränkt sich die Forschung zu diesem Thema meist auf einfache Systeme mit wenigen Freiheitsgraden. In dieser Arbeit wird ein neuer Ansatz zur Ganzkörperbewegungsplanung vorgeschlagen. Durch die Verwendung eines Weltmodells wird die Gelenkkonfiguration auf Stabilität entlang des Pfades optimiert. Die vorgeschlagene Methode bewertet, ob eine sichere Überwindung möglich ist und generiert einen Bewegungsplan, der es dem Roboter erlaubt, generische Hindernisse ohne Umkippen zu überqueren. Kollisionen werden verhindert, indem sie als Nebenbedingungen der Optimierung modelliert werden. Dieser Ansatz wird an einem Kettenfahrzeug mit verstellbaren Flippern und einem fünfgelenkigen Manipulatorarm ausgewertet. Die vorgeschlagene Methode nutzt die Flipper, um den Bodenkontakt zu maximieren, und den Arm, um den Massenschwerpunkt zu verschieben. Zusätzlich verfügt die Plattform über verschiedene Sensoren, um die Umgebung wahrzunehmen. Die Performance der Ganzkörperbewegungsplanung wird in der Simulation und am realen Roboter ausgewertet. In mehreren Szenarien wird gezeigt, dass der Ansatz Umkippen verhindert und die Stabilität des Roboters erhöht. German
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Available Versions of this Item

• Whole-Body Planning for Obstacle Traversal with Autonomous Mobile Ground Robots. (deposited 10 Dec 2018 11:50)
  • Whole-Body Planning for Obstacle Traversal with Autonomous Mobile Ground Robots. (deposited 06 Jun 2019 06:06) [Currently Displayed]

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