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dc.contributor.author
Wermelinger, Martin
dc.contributor.supervisor
Hutter, Marco
dc.contributor.supervisor
Kohler, Matthias
dc.contributor.supervisor
Napp, Nils
dc.contributor.supervisor
Zeilinger, Melanie
dc.date.accessioned
2022-01-10T07:21:02Z
dc.date.available
2022-01-07T15:31:55Z
dc.date.available
2022-01-10T07:21:02Z
dc.date.issued
2021
dc.identifier.uri
http://hdl.handle.net/20.500.11850/523941
dc.identifier.doi
10.3929/ethz-b-000523941
dc.description.abstract
Robotic technology has entered many new fields and applications in the last years and decades, from automated manufacturing, over warehouse logistics, to inspec- tion of industrial sites. While automation and robotics are pushing more and more from industrial to everyday applications, one sector has fallen behind in adapting to those new technologies, the construction sector. Although there is a labor short- age in construction, it still has one of the most considerable unused potentials for automation. Exploiting on-site robotics is not only a great opportunity to resolve the high demand for labor and to increase productivity, but it also has the potential to enable architectural designs that exceed the size and complexity practical with conventional methods. It also offers the opportunity to leverage context-specific, locally sourced materials that are inexpensive, abundant, and low in embodied en- ergy. However, it is still unclear what exact technologies are required and how such robot solutions would potentially look like at this stage. This thesis addresses the development of manipulation skills for a mobile ma- nipulator to detect and assemble arbitrary solid material in a cluttered and unstruc- tured environment like a construction site. The focus lies on the perception of the environment, modeling object instances, and grasping and assembling objects. We are especially interested in manipulating raw material, like stones and boulders, in the context of robotic landscaping, as it targets applications in dangerous-to-access or remote locations undesired for human operators. In this work, we investigate the task of executing autonomous missions in unseen environments at different scales and from stationary to mobile applications. Be- sides localization, obstacle detection, and navigation methods for the mobile base, we introduce a compliant manipulator to perform interaction tasks. The compli- ance gives impact robustness and the capability of controlling contact wrenches ac- curately but comes with limited actuator bandwidth causing tracking performance loss. We address this problem by including the actuator dynamics in a receding horizon control formulation improving tracking and disturbance rejection and show that the natural stiffness of the manipulator can be preserved. The ultimate target of this work is the construction of large-scale structures in real-world outdoor scenarios, outside of well-defined laboratory settings, compli- cating the handling of previously unseen irregularly shaped objects. We contribute by presenting a perception and grasp pose planning pipeline for autonomous ma- nipulation of objects of interest with a robotic walking excavator. A mapping sys- tem incrementally builds a temporally and spatially consistent LiDAR-based map of the robot’s surroundings. It provides the ability to register externally recon- structed point clouds of the scene, e.g., from images captured by a drone-borne camera, helping to increase map coverage. Our grasp planning method utilizes point clouds and mesh surface reconstruction of stones to plan grasp configura- tions with a 2-jaw gripper mounted on the excavator. Besides taking into account the geometry of the stone to sample force closure grasps, the grasp planner consid- ers collision constraints during object pick and place, informed by the LiDAR-based point cloud map. Furthermore, we show an approach to reorient arbitrarily shaped objects that cannot be directly placed at the desired location without violating col- lision constraints. Finally, the presented manipulation methods are combined with geometric target pose planning to compute structurally stable object compositions following a target design. We create a novel process that takes the digitized object model in a physics simulation to find settled placement poses and assess stability, alternately with a 3D shape matching to the target geometry. The locations of the placed objects are refined and updated in simulation to have an accurate digital twin of the scene. Our approach has been thoroughly validated on several interdisciplinary collabo- rations building vertical stone towers in a table-top setup and dry-stone walls com- posed of over one hundred stones with an average weight above 1000 kg with the autonomous excavator HEAP.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-sa/4.0/
dc.subject
Manipulation
en_US
dc.subject
ROBOT CONTROL
en_US
dc.subject
Grasping and Manipulation
en_US
dc.subject
Digital fabrication (dfab)
en_US
dc.subject
Perception and autonomy
en_US
dc.title
Robust Robotic Aggregation of Irregularly Shaped Objects
en_US
dc.type
Doctoral Thesis
dc.rights.license
Creative Commons Attribution-ShareAlike 4.0 International
dc.date.published
2022-01-10
ethz.size
204 p.
en_US
ethz.code.ddc
DDC - DDC::6 - Technology, medicine and applied sciences::600 - Technology (applied sciences)
en_US
ethz.code.ddc
DDC - DDC::6 - Technology, medicine and applied sciences::620 - Engineering & allied operations
en_US
ethz.grant
NCCR Digital Fabrication
en_US
ethz.identifier.diss
27690
en_US
ethz.publication.place
Zurich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09570 - Hutter, Marco / Hutter, Marco
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09570 - Hutter, Marco / Hutter, Marco
en_US
ethz.grant.agreementno
--
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
NCCR (NFS)
ethz.date.deposited
2022-01-07T15:32:00Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2022-01-10T07:21:09Z
ethz.rosetta.lastUpdated
2022-03-29T17:25:33Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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