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Smart Anything Everywhere

Cyber-Physical Systems Engineering Labs is part of the Smart Anything Everywhere initiative.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644400.

RAST (Risk Analysis and Simulation Testing for Agricultural Robots)

Problem and solution

Agricultural robots have emerged as innovative and eco-friendly means for easier farming. In particular, autonomous weeding allows farmers to efficiently maintain their crops without using herbicides or chemical weed control products. Electrically-driven robots require less energy than a tractor. They are also lighter than a tractor in order to avoid compacting the soil, even when used frequently.

Naïo Technologies is a pioneering SME in this domain. Their first product was Oz, a weeding robot for small crops of vegetables. The company is now targeting the market of large-scale vegetable crops and vineyards, and has started the development of bigger and faster robots. However, the deployment of such robots introduces new potential risks to the users and their farm. Since the safety regulations and standards are not yet established for autonomous robots in agriculture, SMEs like Naïo need to adopt a proactive approach in the acquisition of dependability-related technologies. The RAST experiment of CPSE Labs focused on safety analysis and validation technologies, which are crucial for bridging the gap from robot prototypes to mature products.

How did CPSE Labs Help?

The experiment successfully met the objectives pursued by Naïo:

  • To gain a better understanding of the risks induced by the robots and of the principled methods to identify these risks. Naïo increased its safety skills and could get relevant feedback for its robots.
  • To improve the cost-effectiveness of the validation process - Naïo developed simulators allowing for tests that are less costly, more diverse and more controllable than the ones realized in the field.

CPSE Labs provided Naïo with access to leading edge safety methods such as HAZOP-UML for the analysis of the operational risks induced by the robots and Altarica for the assessment of candidate robot architectures. It also helped Naïo to establish simulation-based testing as an essential part of their validation process, based on recent research results on testing robots in virtual worlds.

The experiment facilitated the technology transfer by focusing on concrete problems relevant to Naïo: in addition to offering specialized training sessions, the Design Center also provided technical support on the application of the technologies to the target robots.


An immediate impact of the experiment was a one-third reduction in validation costs, for the functionalities that can be tested with the developed simulators. Naïo now use simulation-based testing for two robots out of the four they have in development.

The expertise gained in safety-related technologies serves longer-term purposes. Indeed, Naïo plans to externalize part of the safety and reliability assessment activities in the future. The experiment gave them the background required to define and subsequently monitor those activities externalized to subcontractors. Overall, the acquisition of safety background puts Naïo into a better position to get into the market of large-scale crop maintenance. Meeting legal requirements, in particular as regards safety, is a prerequisite for selling their robots at the European and international levels.

The RAST experiment was part of Naïo continuous effort to reach the business objective of doubling their turnover each year. They expect to go from €1.2M this year and 40 robots sold, to more than €10M of turnover and 300 robots in 2020. This ambitious objective is in line with the huge potential for development in agricultural robotics. Tractica, a US research organization, forecasts that the agricultural robot market will increase exponentially from $3 billions in 2015 to $16 billions in 2020 and then $73 billions in 2024.


Several dissemination events have taken place to share the results of the experiment:
  • SHARC17 on June 29th 2017
  • FMF on October 10th 2017
  • FIRA (International Forum of Agricultural Robotics) on November 29th & 30th 2017
  • Move your Robot (student competition for professional robotics) during FIRA 2017 event
The simulator developed for the Oz robot during the experiment is open source and available online. A video of the simulation is also available online. This simulator has also been used for the "Move your robot" contest.
Design centre

This experiment is supported by our France design centre

France design centre

Technology platforms


Naio Technologies Logo


1st Nov 2016 - 31st Oct 2017
Funded under: CPSE Labs Call 3