Robotics in Forest Inventories: SPOT’s First Steps

Abstract

In the context of the potential future use of unmanned ground vehicles for forest inventories, we present the first experiences with SPOT, a legged robot equipped with a LiDAR instrument and several cameras that have been used with a teleoperation approach for single-tree detection and measurements. This first test was carried out using the default LiDAR system (the so-called enhanced autonomy payload-EAP, installed on the board of SPOT to guide autonomous movements) to understand advantages and limitations of this platform to support forest inventory activities. The test was carried out in the Vallombrosa forest (Italy) by assessing different data acquisition methods. The first results showed that EAP LiDAR generated noisy point clouds where only large trees (DBH ≥ 20 cm) could be identified. The results showed that the accuracy in tree identification and DBH measurements were strongly influenced by the path used for data acquisition, with average errors in tree positioning no less than 1.9 m. Despite this, the best methods allowed the correct identification of 97% of large trees.

The semiochemical push‐and‐pull technique can reduce bark beetle damage in disturbed Norway spruce forests affected by the Vaia storm

“…The Vaia storm occurred in October 2018 in the Eastern Alps, felling about 16 million m 3 of spruce (Chirici et al, 2019). The storm damaged mainly pure and mature spruce stands creating large wind ‘clear‐cut’ areas, where all trees were broken or uprooted.…”

Robotics for Heritage Surveying: preliminary test on Leica BLK ARC & Spot® toward autonomous 3D mapping

“…The mean error in scans registration for the Faro S-350 with Spot was double the error of the same acquisitions performed with the same scanner in a static mode mounted on a tripod, but in any case, less than 2 mm. Chirici (Chirici et al, 2023) applied Spot® for tree diameter estimation. Seven different tele-piloted paths (one-way, backand-forth with low and medium speeds, diamond, zig-zag, spiral, and four-petal) were analyzed with the integrated Velodyne VLP-16 LiDAR, reporting a point density varying between 41 and 152 points/m2 and a Root Mean Square (RMS) error percentage between 40 and 57 in respect to trees diameters measured with total station used as reference.…”

“…Regarding tree positioning, the absolute error recorded by Spot® varies between 0.002 and 8.1 m. This research reports that trees with a diameter of less than 20 cm were not identified, and authors noticed a high influence on the positioning and density results according to the followed path, pointing at the spiral one as the best. Spot® (Chirici, 2023) is a quadruped robot developed by Boston Dynamics (now Spot v4.0.0 Release) in order to operate autonomously or with assisted missions based on self-positioning and trajectory execution in the mapped environment and to collect multiple data based on sensors equipment. Thanks to its legs, Spot® is able to walk on steep terrains and stairs and the elevated mobility is surely its promising feature.…”

A Seedling Collection Unit of a Mobile Automatic Device for Forest Tree Planting—An Extended Operating Concept

“…The most important one is the necessity to meet the needs of the Earth's growing population for wood, used to produce consumer goods, such as paper, furniture, construction materials, etc. Further needs are related to the necessity to introduce principles of sustainable forest production that will ensure the safety of forest workers, support environmental balance and guarantee the above-mentioned sufficient level of productivity [4]. The implementation of these principles is best achieved by introducing automatic machines in forestry production [5], especially for those tasks that require manual labor-including planting, which is characterized by a high energy input [6][7][8].…”

“…The implementation of these principles is best achieved by introducing automatic machines in forestry production [5], especially for those tasks that require manual labor-including planting, which is characterized by a high energy input [6][7][8]. These level of productivity [4]. The implementation of these principles is best achieved by introducing automatic machines in forestry production [5], especially for those tasks that require manual labor-including planting, which is characterized by a high energy input [6][7][8].…”