Major infrastructure works require the transportation of bulk materials in a continuously changing environment with a never-ending list of hurdles that make it a dangerous working space.
The transportation has been done so far with vehicles driven by people responsible for both their own safety and the rest of the workers.
Ferrovial is looking for a small autonomous mobile robot prototype using e.g. commercial robotic platforms type Arduino, and adding sensors, software, etc. to move around a work-simulated environment (small-scale):
- Trips to several procurement and destination spots.
- Repetitive trips.
- Change of conditions and obstacles during transportation.
- Slopes and risk of fallings.
- Fixed obstacles such as piles of sand or gravel accumulated prefabs, fallen materials or detached rocks.
- Moving obstacles like other vehicles or people passing by.
See the challenge introductory video here!
All kinds of technologies can be used, with sensors or cameras both on the very prototype or on a drone/mother vehicle leading the way. Furthermore, IOT can also be used in other vehicles, people or objects that facilitate the detection by communicating with the prototype.
The participation in the challenge can be either individual or in teams!
This is a 3-round competition:
1st Round – Before 22 Jan
Submit a brief written description of your solution along with a photo/video of your prototype so that it can be evaluated. In addition, please send as well a 15 second video of yourself describing very briefly your project and introducing yourself (or your team).
Semifinals and Finals – 2-3 Feb
Semifinalists will join us at Global Robot Expo Madrid (Spain) by Feb 2. We have some budget to cover travel expenses (300 €/submission). Participants will get free tickets to come to Global Robot Expo.
There will be a few tests that the robots need to pass, like going from point A to point B without bumping into any fixed or moving obstacle.
1st Prize: 2.000 €
2nd and 3rd finalists: 600 € each
+ Tickets to Global Robot Expo Madrid!