The forest industry is constantly striving to increase productivity and cut costs, and many research and innovation projects are currently focusing on semi-automated or autonomous systems. A key element, with several possible solutions, is automated log grasping, where researchers and manufacturers are looking for efficient and sturdy ways to solve the task in real-time forwarding operations. This study presents a simple method for automated log grasping using only a single stereo camera for object detection (log and grapple) and a simple controller moving the boom, with feedback from the camera as boom-tip control. The accuracy, precision, and repeatability of the method was tested on a full-scale forwarder. Boom movements were examined from two different start positions in relation to the target position, with the log placed at three different angles. The overall log-grasping success was also evaluated. The tests were performed in a full-scale, real-time operation, without hand-eye calibration or other sensor data from the machine. The method was precise, with high repeatability, but the grasping point showed a minor systematic offset, depending on log angle. However, the deviation in accuracy was too small to affect the success rate. In practice, the most difficult log angles can be avoided by moving the machine slightly. The log grasping method may become part of an autonomous forwarding system or could provide operator support in semi-automated systems.
Technological development gives forest companies opportunities to maintain competitiveness in the highly cost-sensitive market for forest products. However, no previous studies have examined the technological development decisions made by forest companies or the support tools used when making them. We therefore aimed to describe and analyze 1) the processes used when making such decisions, 2) the associated decision situations, and 3) the use of and need for decision support tools in these processes, with a harwarder concept as case. Semi-structured interviews were conducted with respondents from six forestry organizations. Two theoretical frameworks were used to analyze the interviews, one for unstructured decision processes and one for decision situations. The respondents’ descriptions of their decision processes were consistent with those observed in other industries, and it was shown that decision-making could potentially be improved by investing more resources into diagnosing the problem at hand. The main objective in decision-making was to maximize economic criteria while satisfying threshold requirements relating to criteria such as operator well-being, soil rutting, and wood value. When facing large uncertainties, interviewees preferred to gather data through operational trials and/or scientific studies. If confronted with large uncertainties that could not be reduced, they proceeded with development only if the potential gains exceeded the estimated uncertainties, and implemented innovations in a stepwise manner. These results indicate a need for greater use of existing decision-support tools such as problem-structuring methods to enable more precise diagnoses, simulations to better understand new innovations, and optimization to better evaluate their theoretical large-scale potential.