Implementation of an optimised autonomous Arduino-based car
Autonomous vehicles can be a key feature to sustainable mobility since they promise optimised routes, more efficient fuel consumption, safer road transport, and the ability to alter the perception of driving. This paper describes the implementation of a low-cost, self-navigating Arduino-based model car. The model car utilises an Arduino Uno mainboard. Four DC motors with their corresponding wheels are embedded in the model car to ensure its movement. Furthermore, the model car has an ultrasonic sensor to detect and avoid obstacles. Moreover, the model car hosts an action camera to record its environment, and more features may be added later for artificial cognition. Its chassis is designed and optimised to accommodate all the electronic components and ensure movement. Different versions of the chassis were fabricated using 3D printing technology. The performance of the model car was assessed while navigating in three different scenarios, during which the effect of the speed of the model car and the efficiency of its ultrasonic sensor were evaluated. The paper concludes with the topology optimisation of the chassis of the model car to optimise the chassis compliance and consequently improve the navigation characteristics of the model car.
Authors
- Clio Vossou (ORCID: https://orcid.org/0000-0002-4665-7759)
- Dimitrios Koulocheris (ORCID: https://orcid.org/0000-0002-1379-5805)
- Ioanna Konstantinou
Institutions
- National Technical University of Athens (GR)
Publication Details
- Journal
- Cognitive Sustainability
- Published
- 2025-06-30
- DOI
- https://doi.org/10.55343/cogsust.150
- Citations
- 1
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 1.28