Laser data and algorithms reveal trees with sweep

Research shows that logging methods which take the sweep of trees into account, increase the value of the forest. An automated decision-support system that adapts the felling process to the shape of the trees, is currently being developed. It also reduces the workload for machine operators.

Hi there Nils Lindgren, researcher at Skogforsk. With support from Mistra Digital Forest, you have been investigating whether it is possible to detect trees with sweep using laser sensors on harvesters. What have you figured out?

– That it is a perfectly feasible, interesting avenue to explore, given that sensors are developing rapidly and the technology is constantly becoming both cheaper and better. We have carried out a proof of concept which, in simplified terms, shows that laser data and algorithms can be used to create a three-dimensional model of the forest that detects trees with sweep. However, both the calculation methods and the hardware need further development before we have a solution that controls how the trunks are cut in real time.

The industry is calling for decision-support tools that can detect sweep during felling. Why?

– An autonomous solution would mean that both forestry operations and sawmills would become more resource-efficient. At present, a great deal of value is lost when the felling of trees with sweep is based solely on their length and diameter. Ignoring the shape of the trees causes enormous amounts of waste in the value chain. Increased automation can also make machine operators’ daily work easier. They have a complex job continually requiring many decisions, plus it is almost impossible to spot a tree with sweep with the naked eye.

How far has the development of the hardware progressed?

– The laser scanners currently being fitted to harvesters are prototypes still in development. As part of the project, we are also testing a handheld laser scanner that is already available on the market. It provides high quality data and offers a glimpse of how harvesters with built-in laser sensors are likely to perform in the near future. In the project, we have worked closely with Komatsu Forest, which is developing the actual hardware in the form of a robust sensor. A sensor in this environment must be able to withstand quite extreme conditions, with a lot of vibration and occasionally harsh weather conditions.

What happens next?

– To move towards implementation, we need to develop the computational method so that it is stable and efficient. It has to be fast. The system can’t just stop and think during a felling operation. We will also be testing sensors of varying quality to obtain better laser data, and in this way get closer to a usable product. In addition, the results contribute to a separate project outside Mistra Digital Forest, that is developing laser sensors for retrofitting on harvesters. Perhaps this might be a first step towards providing the support to the machine operators.