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Evaluation of a robotic testing dashboard (RTD) used to compare autonomous robots with human pilots

Autonomous robots are becoming a bigger part of our society. This thesis aims to evaluate a robot testing dashboard (RTD) that can be used as a new way of finding improvements when developing autonomous robots that do not use machine learning. The method that is used is design science research, which is used when creating and evaluating an artifact to address a practical problem. In our case the artifact isthe RTD. This project was performed at a company called Greenworks, which among other things develops and sells autonomous lawn mowers. The company wants to find new testing methods to help develop their autonomous lawnmowers. The RTD is created to visualize the inputs that the lawn mower utilizes to perform its tasks. A human pilot will then control the lawn mower, by only looking at that visualized data. If the pilot using the RTD can execute the same tasks as the lawn mower in its autonomous mode, the test results can be analyzed to see whether the human has done some parts of the tasks differently. The best outcome from the analysis of the test results is to find areas of improvement that can be implemented into the autonomous lawn mower design, both in software and hardware. For this purpose, an RTD was built and tested at Greenworks. From the tests using the RTD we concluded that it is helpful in the testing process, and we could find areas of improvements after analysis of our tests. However, the use of the RTD will require more time and resources compared to other methods. Each company that uses a similar dashboard concept will have to evaluate if the benefits are worth the time. Furthermore, the concept may not suit all areas of robotics but does seem to suit situations where a human can have an advantage over robots, such as in creative problem solving.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hj-54819
Date January 2021
CreatorsBergenholtz, Claes, Isacsson, John
PublisherJönköping University, JTH, Avdelningen för datavetenskap, Jönköping University, JTH, Avdelningen för datateknik och informatik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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