Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot
Planetary exploration scenarios illustrate the need for autonomous robots that are capable to operate in unknown environments without direct human interaction. At the DARPA Robotics Challenge, we demonstrated that our Centaur-like mobile manipulation robot Momaro can solve complex tasks when teleope...
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2016-10-01
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Series: | Frontiers in Robotics and AI |
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Online Access: | http://journal.frontiersin.org/Journal/10.3389/frobt.2016.00057/full |
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author | Max Schwarz Marius Beul David Droeschel Sebastian Schüller Arul Selvam Periyasamy Christian Lenz Michael Schreiber Sven Behnke |
author_facet | Max Schwarz Marius Beul David Droeschel Sebastian Schüller Arul Selvam Periyasamy Christian Lenz Michael Schreiber Sven Behnke |
author_sort | Max Schwarz |
collection | DOAJ |
description | Planetary exploration scenarios illustrate the need for autonomous robots that are capable to operate in unknown environments without direct human interaction. At the DARPA Robotics Challenge, we demonstrated that our Centaur-like mobile manipulation robot Momaro can solve complex tasks when teleoperated. Motivated by the DLR SpaceBot Cup 2015, where robots should explore a Mars-like environment, find and transport objects, take a soil sample, and perform assembly tasks, we developed autonomous capabilities for Momaro. Our robot perceives and maps previously unknown, uneven terrain using a 3D laser scanner. Based on the generated height map, we assess drivability, plan navigation paths, and execute them using the omnidirectional drive. Using its four legs, the robot adapts to the slope of the terrain. Momaro perceives objects with cameras, estimates their pose, and manipulates them with its two arms autonomously. For specifying missions, monitoring mission progress, on-the-fly reconfiguration, and teleoperation, we developed a ground station with suitable operator interfaces. To handle network communication interruptions and latencies between robot and ground station, we implemented a robust network layer for the ROS middleware. With the developed system, our team NimbRo Explorer solved all tasks of the DLR SpaceBot Camp 2015. We also discuss the lessons learned from this demonstration. |
first_indexed | 2024-12-22T11:04:47Z |
format | Article |
id | doaj.art-7df59a6c387e41bf8f189f50f2f615a1 |
institution | Directory Open Access Journal |
issn | 2296-9144 |
language | English |
last_indexed | 2024-12-22T11:04:47Z |
publishDate | 2016-10-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Robotics and AI |
spelling | doaj.art-7df59a6c387e41bf8f189f50f2f615a12022-12-21T18:28:22ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442016-10-01310.3389/frobt.2016.00057186833Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like RobotMax Schwarz0Marius Beul1David Droeschel2Sebastian Schüller3Arul Selvam Periyasamy4Christian Lenz5Michael Schreiber6Sven Behnke7University of BonnUniversity of BonnUniversity of BonnUniversity of BonnUniversity of BonnUniversity of BonnUniversity of BonnUniversity of BonnPlanetary exploration scenarios illustrate the need for autonomous robots that are capable to operate in unknown environments without direct human interaction. At the DARPA Robotics Challenge, we demonstrated that our Centaur-like mobile manipulation robot Momaro can solve complex tasks when teleoperated. Motivated by the DLR SpaceBot Cup 2015, where robots should explore a Mars-like environment, find and transport objects, take a soil sample, and perform assembly tasks, we developed autonomous capabilities for Momaro. Our robot perceives and maps previously unknown, uneven terrain using a 3D laser scanner. Based on the generated height map, we assess drivability, plan navigation paths, and execute them using the omnidirectional drive. Using its four legs, the robot adapts to the slope of the terrain. Momaro perceives objects with cameras, estimates their pose, and manipulates them with its two arms autonomously. For specifying missions, monitoring mission progress, on-the-fly reconfiguration, and teleoperation, we developed a ground station with suitable operator interfaces. To handle network communication interruptions and latencies between robot and ground station, we implemented a robust network layer for the ROS middleware. With the developed system, our team NimbRo Explorer solved all tasks of the DLR SpaceBot Camp 2015. We also discuss the lessons learned from this demonstration.http://journal.frontiersin.org/Journal/10.3389/frobt.2016.00057/fullnavigationMappingMobile manipulationPerception for Grasping and ManipulationSpace Robotics and Automation |
spellingShingle | Max Schwarz Marius Beul David Droeschel Sebastian Schüller Arul Selvam Periyasamy Christian Lenz Michael Schreiber Sven Behnke Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot Frontiers in Robotics and AI navigation Mapping Mobile manipulation Perception for Grasping and Manipulation Space Robotics and Automation |
title | Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot |
title_full | Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot |
title_fullStr | Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot |
title_full_unstemmed | Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot |
title_short | Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot |
title_sort | supervised autonomy for exploration and mobile manipulation in rough terrain with a centaur like robot |
topic | navigation Mapping Mobile manipulation Perception for Grasping and Manipulation Space Robotics and Automation |
url | http://journal.frontiersin.org/Journal/10.3389/frobt.2016.00057/full |
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