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Path planning for reconfigurable hTetro robot combining heat conduction-based and discrete optimization

Do, Huy ; Vu, Le Anh ; Weeger, Oliver ; Mohan, Rajesh Elara ; Guo, Yujie ; Nguyen, Tan Nhat ; Vu, Minh Bui ; Duc, Phan Van (2021)
Path planning for reconfigurable hTetro robot combining heat conduction-based and discrete optimization.
In: IEEE Access, 9
doi: 10.26083/tuprints-00019882
Artikel, Zweitveröffentlichung, Verlagsversion

Kurzbeschreibung (Abstract)

Self-reconfigurable robots present advanced solutions for various automation applications in domains, e.g., planetary exploration, rescue missions, cleaning, and maintenance. These robots have the ability to change their morphology according to given requirements or adapt to new circumstances, which, for example, can overcome constraints while navigating within a working environment. However, the autonomous navigation of self-reconfigurable robots is more complex than that of robots with fixed shape because of the intrinsic complexity of robot motions, especially in complicated obstacle environments. To address this challenge, we present a novel path planning method for reconfigurable robots in this study. The technique is inspired by the similarity between a robot motion path and a heat conduction path at the steady-state. In the heat transfer analysis domain, feasible moving locations are modeled as materials with high conductivity, while obstacles are considered thermal insulators, and the initial and destination positions are assigned as heat sink and heat source, respectively. The temperature profile and gradient calculated by finite element analysis are used to indicate the possible moving directions from the heat sink to the heat source. Based on the temperature gradient ascent, a step-wise conductivity reaching algorithm is developed to optimize robot paths using customized multi-objective functions that take the costs of morphology changes, path smoothness, and safety into account. The proposed path planning method is successfully applied to the hinged-tetro self-reconfigurable robot and demonstrated on several virtual environments and a real-world testbed environment.

Typ des Eintrags: Artikel
Erschienen: 2021
Autor(en): Do, Huy ; Vu, Le Anh ; Weeger, Oliver ; Mohan, Rajesh Elara ; Guo, Yujie ; Nguyen, Tan Nhat ; Vu, Minh Bui ; Duc, Phan Van
Art des Eintrags: Zweitveröffentlichung
Titel: Path planning for reconfigurable hTetro robot combining heat conduction-based and discrete optimization
Sprache: Englisch
Publikationsjahr: 2021
Verlag: IEEE
Titel der Zeitschrift, Zeitung oder Schriftenreihe: IEEE Access
Jahrgang/Volume einer Zeitschrift: 9
DOI: 10.26083/tuprints-00019882
URL / URN: https://tuprints.ulb.tu-darmstadt.de/19882
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Herkunft: Zweitveröffentlichungsservice
Kurzbeschreibung (Abstract):

Self-reconfigurable robots present advanced solutions for various automation applications in domains, e.g., planetary exploration, rescue missions, cleaning, and maintenance. These robots have the ability to change their morphology according to given requirements or adapt to new circumstances, which, for example, can overcome constraints while navigating within a working environment. However, the autonomous navigation of self-reconfigurable robots is more complex than that of robots with fixed shape because of the intrinsic complexity of robot motions, especially in complicated obstacle environments. To address this challenge, we present a novel path planning method for reconfigurable robots in this study. The technique is inspired by the similarity between a robot motion path and a heat conduction path at the steady-state. In the heat transfer analysis domain, feasible moving locations are modeled as materials with high conductivity, while obstacles are considered thermal insulators, and the initial and destination positions are assigned as heat sink and heat source, respectively. The temperature profile and gradient calculated by finite element analysis are used to indicate the possible moving directions from the heat sink to the heat source. Based on the temperature gradient ascent, a step-wise conductivity reaching algorithm is developed to optimize robot paths using customized multi-objective functions that take the costs of morphology changes, path smoothness, and safety into account. The proposed path planning method is successfully applied to the hinged-tetro self-reconfigurable robot and demonstrated on several virtual environments and a real-world testbed environment.

Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-198827
Zusätzliche Informationen:

Self-reconfigurable robot, tiling robotics, multi-objective path planning, heat conduction, mobile robot

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Fachgebiet Cyber-Physische Simulation (CPS)
Hinterlegungsdatum: 15 Dez 2021 10:29
Letzte Änderung: 16 Dez 2021 06:40
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