Pajarinen, Joni ; Arenz, Oleg ; Peters, Jan ; Neumann, Gerhard (2022)
Probabilistic Approach to Physical Object Disentangling.
In: IEEE Robotics and Automation Letters, 2020, 5 (4)
doi: 10.26083/tuprints-00022927
Artikel, Zweitveröffentlichung, Postprint
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Kurzbeschreibung (Abstract)
Physically disentangling entangled objects from each other is a problem encountered in waste segregation or in any task that requires disassembly of structures. Often there are no object models, and especially with cluttered irregularly shaped objects, the robot cannot create a model of the scene due to occlusion. One of our key insights is that based on previous sensory input we are only interested in moving an object out of the disentanglement around obstacles. That is, we only need to know where the robot can successfully move in order to plan the disentangling. Due to the uncertainty we integrate information about blocked movements into a probability map. The map defines the probability of the robot successfully moving to a specific configuration. Using as cost the failure probability of a sequence of movements we can then plan and execute disentangling iteratively. Since our approach circumvents only previously encountered obstacles, new movements will yield information about unknown obstacles that block movement until the robot has learned to circumvent all obstacles and disentangling succeeds. In the experiments, we use a special probabilistic version of the Rapidly exploring Random Tree (RRT) algorithm for planning and demonstrate successful disentanglement of objects both in 2-D and 3-D simulation, and, on a KUKA LBR 7-DOF robot. Moreover, our approach outperforms baseline methods.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Pajarinen, Joni ; Arenz, Oleg ; Peters, Jan ; Neumann, Gerhard |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Probabilistic Approach to Physical Object Disentangling |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2020 |
| Verlag: | IEEE |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Robotics and Automation Letters |
| Jahrgang/Volume einer Zeitschrift: | 5 |
| (Heft-)Nummer: | 4 |
| Kollation: | 9 ungezählte Seiten |
| DOI: | 10.26083/tuprints-00022927 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/22927 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | Physically disentangling entangled objects from each other is a problem encountered in waste segregation or in any task that requires disassembly of structures. Often there are no object models, and especially with cluttered irregularly shaped objects, the robot cannot create a model of the scene due to occlusion. One of our key insights is that based on previous sensory input we are only interested in moving an object out of the disentanglement around obstacles. That is, we only need to know where the robot can successfully move in order to plan the disentangling. Due to the uncertainty we integrate information about blocked movements into a probability map. The map defines the probability of the robot successfully moving to a specific configuration. Using as cost the failure probability of a sequence of movements we can then plan and execute disentangling iteratively. Since our approach circumvents only previously encountered obstacles, new movements will yield information about unknown obstacles that block movement until the robot has learned to circumvent all obstacles and disentangling succeeds. In the experiments, we use a special probabilistic version of the Rapidly exploring Random Tree (RRT) algorithm for planning and demonstrate successful disentanglement of objects both in 2-D and 3-D simulation, and, on a KUKA LBR 7-DOF robot. Moreover, our approach outperforms baseline methods. |
| Freie Schlagworte: | Robot sensing systems, Collision avoidance, Path planning, Planning, Probabilistic logic, Task analysis, Autonomous systems, collision avoidance, intelligent robots, path planning, probabilistic computing, waste recovery |
| Status: | Postprint |
| URN: | urn:nbn:de:tuda-tuprints-229277 |
| Zusätzliche Informationen: | Video attachment: https://t1p.de/r1a6d The video illustrates the proposed approach for disentangling an object from other unknown objects. |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Intelligente Autonome Systeme |
| Hinterlegungsdatum: | 25 Nov 2022 12:48 |
| Letzte Änderung: | 17 Mai 2023 12:48 |
| PPN: | 503603031 |
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| Suche nach Titel in: | TUfind oder in Google |
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- Probabilistic Approach to Physical Object Disentangling. (deposited 25 Nov 2022 12:48) [Gegenwärtig angezeigt]
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