We consider a benchmark example of a three-link planar biped walker with torso, which is actuated in between the legs. The torso is thought to be kept upright by two identical torsional springs. The mathematical model reflects a three-degree-of-freedom mechanical system with impulse effects, which describe the impacts of the swing leg with the ground, and the aim is to induce stable limit-cycle walking on level ground. The main contribution is a novel systematic trajectory planning procedure for solving the problem of gait synthesis. The key idea is to find a system of ordinary differential equations for the functions describing a synchronization pattern for the time evolution of the generalized coordinates along a periodic motion. These functions, which are known as virtual holonomic constraints, are also used to compute an impulsive linear system that approximates the time evolution of the subset of coordinates that are transverse to the orbit of the continuous part of the periodic solution. This auxiliary system, which is known as transverse linearization, is used to design a nonlinear exponentially orbitally stabilizing feedback controller. The performance of the closed-loop system and its robustness with respect to various perturbations and uncertainties are illustrated via numerical simulations.

This article presents a study on the world's first unmanned machine designed for autonomous forestry operations. In response to the challenges associated with traditional forestry operations, we developed a platform equipped with essential hardware components necessary for performing autonomous forwarding tasks. Through the use of computer vision, autonomous navigation, and manipulator control algorithms, the machine is able to pick up logs from the ground and manoeuvre through a range of forest terrains without the need for human intervention. Our initial results demonstrate the potential for safe and efficient autonomous extraction of logs in the cut‐to‐length harvesting process. We achieved a high level of accuracy in our computer vision system, and our autonomous navigation system proved to be highly efficient. This research represents a significant milestone in the field of autonomous outdoor robotics, with far‐reaching implications for the future of forestry operations. By reducing the need for human labor, autonomous machines have the potential to increase productivity and reduce labor costs, while also minimizing the environmental impact of timber harvesting. The success of our study highlights the potential for further development and optimization of autonomous machines in the forestry industry.

A teleoperation system has been developed for a hydraulic crane, of the type used on a forwarder vehicle, which travels off-road and collects logs cut by a harvester. The system developed consists of a 3D virtual environment, which allows the user to input a desired position for the crane tip using either the mouse or a joystick. The desired position is then transmitted (via UDP/IP) to a local control system. The crane is a redundant manipulator, so movements of the individual links are calculated using a pseudoinverse method, and controlled using PIDs with friction compensation. Encoder data from the crane links are continuously sent back to the user side, and the crane's movement is visualized in the virtual environment. The system has been tested on a real forwarder crane, experimental results and a video of the system's performance are provided.