Project Summary

SINAV (Soluzioni Innovative per la Navigazione Autonoma Veloce) is an ASI-funded activity that aims at researching innovative technologies to increase rover autonomy for Mars exploration. The activity is under development together with Altec, Thales Alenia Space, and PoliTO.

Problem we solved

We are working together with Altec, Thales Alenia Space, and PoliTO to provide autonomous navigation onboard Unmanned rovers for Mars exploration. Autonomous navigation in robotic missions on another planet is a key software element that allows one to plan and follow routes autonomously while mapping the environment and avoiding obstacles. Current AutoNavs for space exploration are typically Stop-and-Go: the rover moves along a planned trajectory for 2-3 meters, stops, computes, and proceeds again, in a loop. The SINAV study aims at finding continuous navigation solutions to increase rover navigation autonomy.

Why it is important

The use of Deep Learning-based algorithms can be used to extract relevant features from the acquired images on Mars to analyze them efficiently. AIKO is working on developing Deep Learning models for rover and drone image analysis. On one hand, rover image processing can provide useful information for navigation purposes and possible scientific exploration. On the other side, drone image processing can be used to identify different types of terrains to generate a detailed traversability map to improve the accuracy and the extension of rover navigation planning. The technology will be demonstrated in a real facility simulating the Mars environment.