Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
From Tele-remote Operation to Semi-automated Wheel-loader
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0001-7395-7557
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0001-5662-825x
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2018 (English)In: International Journal of Electrical and Electronic Engineering and Telecommunications, ISSN 2319-2518, Vol. 7, no 4, p. 178-182Article in journal (Refereed) Published
Abstract [en]

This paper presents experimental results with tele-remote operation of a wheel-loader and proposes a method to semi-automate the process. The different components of the tele-remote setup are described in the paper. We focus on the short loading cycle, which is commonly used at quarry and construction sites for moving gravel from piles onto trucks. We present results from short-loading-cycle experiments with three operators, comparing productivity between tele-remote operation and manual operation. A productivity loss of 42% with tele-remote operation motivates the case for more automation. We propose a method to automate the bucket-filling process, which is one of the key operations performed by a wheel-loader.

Place, publisher, year, edition, pages
2018. Vol. 7, no 4, p. 178-182
Keywords [en]
automation, bucket-filling, construction, quarry, tele-operation, wheel-loader
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Media and Communication Technology
Research subject
Industrial Electronics; Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-71381DOI: 10.18178/ijeetc.7.4.178-182OAI: oai:DiVA.org:ltu-71381DiVA, id: diva2:1259748
Available from: 2018-10-30 Created: 2018-10-30 Last updated: 2018-11-23Bibliographically approved
In thesis
1. Automation of Wheel-Loaders
Open this publication in new window or tab >>Automation of Wheel-Loaders
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Automation av hjullastare
Abstract [en]

Automation and tele-remote operation of mobile earth moving machines is desired for safety and productivity reasons. With tele-operation and automation, operators can avoid harsh ergonomic conditions and hazardous environments with poor air quality, and the productivity can in principle be improved by saving the time required to commute to and from work areas. Tele-remote operation of a wheel-loader is investigated and compared with manual operation, and it is found that the constrained perception of the machine is a challenging problem with remote operations. Real-time video transmission over wireless is difficult, but presents a way towards improving the remote operator’s quality of experience. To avoid glitches in the real-time video, arising from variable wireless conditions, the use of SCReAM (Self-Clocked Rate Adaptation for Multimedia) protocol is proposed. Experiments with a small scale robot over LTE show the usefulness of SCReAM for time-critical remote control applications. Automation of the bucket-filling step in the loading cycle of a wheel-loader has been an open problem, despite three decades of research. To address the bucket-filling problem, imitation learning has been applied using expert operator data, experiments are performed with a 20-tonne Volvo L180H wheel-loader and an automatic bucket-filling solution is proposed, developed and demonstrated in field-tests. The conducted experiments are in the realm of small data (100 bucket-filling examples), shallow time-delayed neural-network (TDNN), and a wheel-loader interacting with a non-stationary pile-environment. The total delay length of the TDNN model is found to be an important hyperparameter, and the trained and tuned model comes close to the performance of an expert operator with slightly longer bucket-filling time. The proposed imitation learning trained on medium coarse gravel succeeds in filling buckets in a gravel cobble pile. However, a general solution for automatic bucket-filling needs to be adaptive to possible changes in operating conditions. To adapt an initial imitation model for unseen operating conditions, a reinforcement learning approach is proposed and evaluated. A deterministic actor-critic algorithm is used to update actor (control policy) and critic (policy evaluation) networks. The experiments show that by use of a carefully chosen reward signal the models learns to improve and maximizes bucket weights in a gravel-cobble pile with only 40 bucket-filling trials. This shows that an imitation learning based bucket-filling solution equipped with a reinforcement learning agent is well suited for the continually changing operating conditions found in the construction industry. The results presented in this thesis are a demonstration of the use of artificial intelligence and machine learning methods for the operation of construction equipment. Wheel-loader OEMs can use these results to develop an autonomous bucket-filling function that can be used in manual, tele-remote or fully autonomous operations.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2018
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Engineering and Technology Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Industrial Electronics
Identifiers
urn:nbn:se:ltu:diva-71460 (URN)978-91-7790-258-4 (ISBN)978-91-7790-259-1 (ISBN)
Public defence
2019-01-31, A1545, Luleå, 10:00 (English)
Opponent
Supervisors
Available from: 2018-11-06 Created: 2018-11-06 Last updated: 2019-02-19Bibliographically approved

Open Access in DiVA

fulltext(867 kB)90 downloads
File information
File name FULLTEXT01.pdfFile size 867 kBChecksum SHA-512
8ef1c6d9d6ebf1aaa3f70ae8774161dc8c1f783b87a16e9b2997f95a150f2eb4b76d8bcbf6bb0590330d32f959811fa64091dc528c932750cfd48a5ec30913ec
Type fulltextMimetype application/pdf

Other links

Publisher's full texthttp://www.ijeetc.com/index.php?m=content&c=index&a=show&catid=189&id=1163

Authority records BETA

Dadhich, SiddharthBodin, UlfSandin, FredrikAndersson, Ulf

Search in DiVA

By author/editor
Dadhich, SiddharthBodin, UlfSandin, FredrikAndersson, Ulf
By organisation
Embedded Internet Systems LabComputer ScienceSignals and Systems
Other Electrical Engineering, Electronic Engineering, Information EngineeringMedia and Communication Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 90 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 93 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf