NI – Natural Intelligence for Robotic Monitoring of Habitats
With the aim to prevent the growing threats to the nature, with the European Green Deal the EU established the paramount importance of environmental monitoring, which today is entirely executed by human operators.
Natural Intelligence project aims to serve the European Green Deal with robots able to accomplish monitoring of natural habitats.
Stretching over 18% of the EU’s land area and almost 6% of its marine territory, Natura 2000 is the largest coordinated network of protected areas in the world. The land and sea coverage will be increased up to 30% within 2030.
The Consortium aims to design the first robotic workforce for monitoring natural habitats in real environments: forests, grasslands, dunes, and alpine scenarios.
NI robots will be empowered by Natural Intelligence, emerging by the interaction of environment, body and mind, leveraging on the fusion of physical and cognitive crucial enablers:
- artificial Cognition that will provide:
- autonomous classification of plants species and natural habitats
- autonomous navigation in natural environments
- effective physical environment-robot interaction through environment-aware impedance planning and bio-inspired anticipatory control
- articulated soft-robotics powered Mechatronics:
- state of the art quadruped robots empowered by adaptive bio-inspired feet for enhanced locomotion and terrain perception
- novel robust-by-design articulated soft robot structures
- long-lasting operation capabilities through efficient exploitation of robot dynamics
The NI approach leverages on the interaction of environment, body and mind and for the first time will put the natural habitat at the centre of the robotics research.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016970.
(In the picture: improving the haptic capabilities, the SoftFoot-Q will aquire the perception of geometrical and interaction quantities. The foot will provide estimates of local inclination and curvature of the ground. Furthermore, it will provide estimates of the contact forces and foot-contact surface).