Ola Ringdahl

Autonomous forest vehicles: historic, envisioned, and state-of-the-art.

Abstract The feasibility of using autonomous forest vehicles (which can be regarded as logical developments in the ongoing automation of forest machines), the systems that could be applied in them, their potential advantages and limitations (in the foreseeable future) are considered in this paper. The goals were to analyze: 1) the factors influencing the degree of automation in logging; 2) the technical principles that can be applied to autonomous forest machines, and 3) the feasibility of developing an autonomous path-tracking forest vehicle. A type of vehicle that is believed to have considerable commercial potential is an autonomous forwarder. The degree of automation is influenced by increased productivity, the machine operator as a bottle-neck, cost reduction, and environmental aspects. Technical principles that can be applied to autonomous forest vehicles are satellite navigation, wheel odometry, laser scanner, and radar. A new path-tracking algorithm has been developed to reduce deviations from the desired path by utilizing the driver’s steering commands. The presented system has demonstrated both possibilities and difficulties associated with autonomous forest machines. A field study has shown that it is quite possible for them to learn and track a path previously demonstrated by an operator with an accuracy of 0.1 m on flat ground and also to detect and avoid unexpected obstacles. Although the forest machine safely avoids obstacles, the study shows that further research in the field of obstacle avoidance is needed to optimize performance and ensure safe operation in a real forest environment.

Development of an Autonomous Forest Machine for Path Tracking

In many respects traditional automation in the forest-machine industry hasreached an upper limit, since the driver already has to deal with an excess ofinformation and take too many decisions at a ...

Enhanced Algorithms for Estimating Tree Trunk Diameter Using 2D Laser Scanner

Accurate vehicle localization in forest environments is still an unresolved problem. Global navigation satellite systems (GNSS) have well known limitations in dense forest, and have to be combined with for instance laser based SLAM algorithms to provide satisfying accuracy. Such algorithms typically require accurate detection of trees, and estimation of tree center locations in laser data. Both these operations depend on accurate estimations of tree trunk diameter. Diameter estimations are important also for several other forestry automation and remote sensing applications. This paper evaluates several existing algorithms for diameter estimation using 2D laser scanner data. Enhanced algorithms, compensating for beam width and using multiple scans, were also developed and evaluated. The best existing algorithms overestimated tree trunk diameter by ca. 40%. Our enhanced algorithms, compensating for laser beam width, reduced this error to less than 12%.

Path tracking in forest terrain by an autonomous forwarder

Abstract Autonomous navigation in forest terrain, where operation paths are rarely straight or flat and obstacles are common, is challenging. This paper evaluates a system designed to autonomously follow previously demonstrated paths in a forest environment without loading/unloading timber, a pre-step in the development of fully autonomous forwarders. The system consisted of a forwarder equipped with a high-precision global positioning system to measure the vehicles heading and position. A gyro was used to compensate for the influence of the vehicles roll and pitch. On an ordinary clear-cut forest area with numerous stumps, the vehicle was able to follow two different tracks, three times each at a speed of 1 m s−1, with a mean path tracking error of 6 and 7 cm, respectively. The error never exceeded 35 cm, and in 90% of the observations it was less than 14 and 15 cm, respectively. This accuracy is well within the necessary tolerance for forestry operations. In fact, a human operator would probably have a hard time following the track more accurately. Hence, the developed systems function satisfactorily when using previously demonstrated paths. However, further research on planning new paths in unknown unstructured terrain and on loading/unloading is required before timber transports can be fully automated.

Real-time path planning using a simulator-in-the-loop

This paper describes the development of a real-time path planner for off-road vehicles using a simulator. The general idea with the presented system is to extend a standard path-tracking algorithm with a simulator that, in real-time, tries to predict collisions in a window forward in time. If a collision is predicted, the vehicle is stopped and a path-search phase is initiated. Variants of the original path are generated and simulated until a feasible path is found. The real vehicle then continues, now tracking the replanned path.

Potentials of possible machine systems for directly loading logs in cut-to-length harvesting

In conventional mechanized cut-to-length systems, a harvester fells and cuts trees into logs that are stored on the ground until a forwarder picks them up and carries them to landing sites. A propo ...In conventional mechanized cut-to-length systems, a harvester fells and cuts trees into logs that are stored on the ground until a forwarder picks them up and carries them to landing sites. A proposed improvement is to place logs directly into the load spaces of transporting machines as they are cut. Such integrated loading could result in cost reductions, shorter lead times from stump to landing, and lower fuel consumption. However, it might also create waiting times for the machines involved, whereas multifunctional machines are likely to be expensive. Thus, it is important to analyze whether or not the advantages of any changes outweigh the disadvantages. The conventional system was compared with four potential systems, including two with autonomous forwarders, using discrete-event simulation with stochastic elements in which harvests of more than 1000 final felling stands (containing in total 1.6 million m3) were simulated 35 times per system. The results indicate that harwarders have substantial pote...

Strategies for Selecting Best Approach Direction for a Sweet-Pepper Harvesting Robot

An autonomous sweet pepper harvesting robot must perform several tasks to successfully harvest a fruit. Due to the highly unstructured environment in which the robot operates and the presence of occlusions, the current challenges are to improve the detection rate and lower the risk of losing sight of the fruit while approaching the fruit for harvest. Therefore, it is crucial to choose the best approach direction with least occlusion from obstacles.

Human Detection Based on Infrared Images in Forestry Environments

It is essential to have a reliable system to detect humans in close range of forestry machines to stop cutting or carrying operations to prohibit any harm to humans. Due to the lighting conditions and high occlusion from the vegetation, human detection using RGB cameras is difficult. This paper introduces two human detection methods in forestry environments using a thermal camera; one shape-dependent and one shape-independent approach. Our segmentation algorithm estimates location of the human by extracting vertical and horizontal borders of regions of interest (ROIs). Based on segmentation results, features such as ratio of height to width and location of the hottest spot are extracted for the shape-dependent method. For the shape-independent method all extracted ROI are resized to the same size, then the pixel values (temperatures) are used as a set of features. The features from both methods are fed into different classifiers and the results are evaluated using side-accuracy and side-efficiency. The results show that by using shape-independent features, based on three consecutive frames, we reach a precision rate of 80 % and recall of 76 %.

Adaptive Image Thresholding of Yellow Peppers for a Harvesting Robot

The presented work is part of the H2020 project SWEEPER with the overall goal to develop a sweet pepper harvesting robot for use in greenhouses. As part of the solution, visual servoing is used to ...