Wandinger, David (2023) Tele Running - Energy Efficient Locomotion for Elastic Joint Robots by Imitation Learning. DLR-Interner Bericht. DLR-IB-RM-OP-2023-70. Bachelorarbeit. University of Applied Sciences Munich.
![]() |
PDF
16MB |
Kurzfassung
This thesis presents an imitation learning approach to energy-efficient trajectory generation for elastic, legged robots. The trajectories are generated by teleoperation with force feedback. The presented framework allows an operator to achieve locomotion on an one-leg hopper by controlling its foot tip. The force feedback is designed to assist the operator to find gaits which exploit the natural harmonics of the hopper and thus improve energy efficiency. The resulting trajectory is approximated, parameterized, and replayed on the robot. The operator achieves a cost of transport of 0.25 at 0.63 m/s, considering the mechanical energy. Black-box optimization is used to keep this value with varying hardware parameters, such as different foot-tip stiffness. A reinforcement learning algorithm stabilizes lateral movement by active balance in simulation. Learning on hardware shows an improvement in stability. The concept is extended to multi-legged robots by teleoperating the two feet of the biped DLR C-Runner in simulation. The force feedback assists the operator to find stable gaits where the center of mass does not leave the support polygon of the feet. On both systems, the presented teleoperation framework utilizes the human's capability of estimating the properties of non-linear dynamics by designing appropriate haptic feedback.
elib-URL des Eintrags: | https://elib.dlr.de/195831/ | ||||||||
---|---|---|---|---|---|---|---|---|---|
Dokumentart: | Berichtsreihe (DLR-Interner Bericht, Bachelorarbeit) | ||||||||
Titel: | Tele Running - Energy Efficient Locomotion for Elastic Joint Robots by Imitation Learning | ||||||||
Autoren: |
| ||||||||
Datum: | 22 Februar 2023 | ||||||||
Referierte Publikation: | Nein | ||||||||
Open Access: | Ja | ||||||||
Status: | veröffentlicht | ||||||||
Stichwörter: | Legged Robots; Cost of Transport; Black-Box Optimization; Reinforcement Learning; Humanoids | ||||||||
Institution: | University of Applied Sciences Munich | ||||||||
Abteilung: | Department of Applied Sciences and Mechatronics | ||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||
HGF - Programm: | Raumfahrt | ||||||||
HGF - Programmthema: | Robotik | ||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||
DLR - Forschungsgebiet: | R RO - Robotik | ||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Laufroboter/Lokomotion [RO] | ||||||||
Standort: | Oberpfaffenhofen | ||||||||
Institute & Einrichtungen: | Institut für Robotik und Mechatronik (ab 2013) > Analyse und Regelung komplexer Robotersysteme | ||||||||
Hinterlegt von: | Wandinger, David | ||||||||
Hinterlegt am: | 04 Jul 2023 12:22 | ||||||||
Letzte Änderung: | 04 Jul 2023 12:22 |
Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags