Data collected between the 10 and the 13 of May 2022, in Valsorda, Gualdo Tadino 06023 (PG), Italy, inside the Natura 2000 SAC IT5210014. The data acquisition has been conducted by a team composed of both robotic engineers and plant scientists. The platform used to collect the data is the ANYmal C quadrupedal robot. The dataset contains two different sets of data: 1) typical and early warning species data - pictures and videos of two different typical species of the habitat 6210 and one early warning species. 2) monitoring mission data - video of the monitoring mission, robot status and point clouds, pictures and videos taken by the robot during the autonomous surveys. This dataset has a multidisciplinary scope and can be used by resear...
Welcome to the UK-RAS White paper Series on Robotics and Autonomous Systems (RAS). This is one of th...
Forest research is essential for understanding the global carbon cycle and multi-scale forest decisi...
Accurate and timely monitoring is imperative to the resilience of forests for economic growth and cl...
Data collected between the 19th and the 21rd of July 2022, in Valfurva, 23030 (SO), Italy, within th...
Data collected between the 16th and the 19th of May 2022, in Platamona, 07037 (SS), Sardinia, Italy,...
Data collected between the 27th and the 28th of April 2022, in Chiusi Della Verna, Arezzo 52010 (AR)...
In this paper, we first discuss the challenges related to habitat monitoring and review possible rob...
In this paper, we first discuss the challenges related to habitat monitoring and review possible rob...
The real-world dataset RumexWeeds targets the detection of the grassland weeds: Rumex obtusifolius...
Automated acquisition of plant eco-phenotypic information can serve as a decisionmaking basis for pr...
It is critical to protect Earth’s biodiversity, not just for its own intrinsic value, but also for t...
Grasslands areas are the second largest land cover type in the Alps ranging from inten...
Life on Earth is threatened by the effects of pollution and global warming. One million over the eig...
A remote-controlled electric robot has been built to inspect the presence of CaLsol in horticultural...
After forested areas grasslands are the second largest land cover type in the Alps ranging from inte...
Welcome to the UK-RAS White paper Series on Robotics and Autonomous Systems (RAS). This is one of th...
Forest research is essential for understanding the global carbon cycle and multi-scale forest decisi...
Accurate and timely monitoring is imperative to the resilience of forests for economic growth and cl...
Data collected between the 19th and the 21rd of July 2022, in Valfurva, 23030 (SO), Italy, within th...
Data collected between the 16th and the 19th of May 2022, in Platamona, 07037 (SS), Sardinia, Italy,...
Data collected between the 27th and the 28th of April 2022, in Chiusi Della Verna, Arezzo 52010 (AR)...
In this paper, we first discuss the challenges related to habitat monitoring and review possible rob...
In this paper, we first discuss the challenges related to habitat monitoring and review possible rob...
The real-world dataset RumexWeeds targets the detection of the grassland weeds: Rumex obtusifolius...
Automated acquisition of plant eco-phenotypic information can serve as a decisionmaking basis for pr...
It is critical to protect Earth’s biodiversity, not just for its own intrinsic value, but also for t...
Grasslands areas are the second largest land cover type in the Alps ranging from inten...
Life on Earth is threatened by the effects of pollution and global warming. One million over the eig...
A remote-controlled electric robot has been built to inspect the presence of CaLsol in horticultural...
After forested areas grasslands are the second largest land cover type in the Alps ranging from inte...
Welcome to the UK-RAS White paper Series on Robotics and Autonomous Systems (RAS). This is one of th...
Forest research is essential for understanding the global carbon cycle and multi-scale forest decisi...
Accurate and timely monitoring is imperative to the resilience of forests for economic growth and cl...