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Master theses

Current and past ideas and concepts for Master Theses.

Advanced sensor technology for robotic lawn mowers: Terrainability

Subject

Background – Robotic lawnmowers are big business in Europe. Global sales of these robots are expected to surpass $3 billion by 2023. One of the reasons people still are reticent about investing in a robotic lawnmower are concerns over safety and security. To deliver outstanding peace of mind, modern robot mower design takes at least as much account of safety as it does grass cutting.

Subject – As cities grow larger and more populous, also the importance of parks and other green spaces is increasing, opening unique opportunities for application of robotic mowers in public spaces. Swarms of professional robotic lawnmowers, operating unsupervised throughout public spaces within the middle of highly urbanized environments, demand a fundamental revision of all product safety aspects. To fulfil this vision and to deal with some of the most demanding challenges in the future of green spaces, robotic lawnmowers need to become even smarter with more intelligent onboard solutions, and more advanced sensors to interact safely with their environment at all times. Effective collision avoidance systems featuring hi-tech sensors will enable future generation robotic mowers to retain minimal safety clearances at all times, alleviating the risks of accidents and injuries for people as well as animals.
For future application in residential and professional robot lawnmowers, VUB spinoff company eXia Belgium N.V. is partnering with the world’s largest outdoor robotics company to evaluate its proprietary biometric sensing technology to avoid near-field collisions.

Kind of work

Terrainability or a robot‘s ability to negotiate various terrain irregularities, also is impacted by the extent to which readings from navigational and safety sensors are affected by undulations in the landscape. This thesis will address the latter aspect in more detail with regard to eXia Belgium’s unique volumetric sensing technology. Thesis work combines extensive field tests integrating sensorics data with FPV imagery and accurate geotagging, with numerical modelling (Comsol/Matlab) of the underlying signal dynamics, and the derivation of advanced signal processing algorithms (Matlab).

Framework of the Thesis

In collaboration with eXia Belgium N.V. – As a spin-off company of the Vrije Universiteit Brussel in collaboration with Imec vzw, eXia Belgium is a global pioneer in the development of electrostatic sensor solutions for near-field collision avoidance. eXia sensors are applied in assisted driving, autonomous vehicles, automotive comfort features and machine safety. With its Active Sideguard turn assist sensors, addressing the risks and dangers of urban traffic, eXia has the aspiration to revolutionize road safety. As a trusted partner for global suppliers and leading technology corporations, eXia also facilitates the development of tailored products to meet specific customer needs.

ETRO – eXia Belgium N.V.
Bart Truyen
E-mail: btruyen@etrovub.be

Promotor

Prof. Hichem Sahli

+32 (0)2 629 2916

hsahli@etrovub.be

more info

Supervisor

  Bart Truyen

+32 (0)2 629 3954

btruyen@etrovub.be

more info

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