We propose a novel method to analyze how human operators use hydraulic manipulators of heavy-duty equipment. The approach is novel in the sense that it applies knowledge of motion planning and optimization techniques used in robotics. As an example, we consider the case of operating a forestry crane. To that end, we use motion data that has been recorded during standard operation with the help of sensors and a data acquisition unit. The data backs up the notion that operators work by performing repeatable patterns observed in the trajectories of the manipulator's joints. We show how this nominal behavior is computed, and consequently, this allows us to present the following: 1) an analytical procedure to analyze motions, 2) how to represent the “performance” of the operator in a 2-D plot, 3) an example of how to use this information to suggest customized control settings, and 4) some complementary ideas needed for improving efficiency through automation.

We analyze the problem of dynamic non-prehensile manipulation by considering the example of the butterfly robot. Our main objective is to study the problem of stabilizing periodic motions, which resemble some form of juggling acrobatics. To this end, we approach the problem by considering the framework of virtual holonomic constraints. Under this basis, we provide an analytical and systematic solution to the problems of trajectory planning and design of feedback controllers to guarantee orbital exponential stability. Results are presented in the form of simulation tests.

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.

We consider the example of a three-link planar biped walker with two passive links. The main objective is to design symmetric periodic gaits in flat ground, that can be exponentially stabilized by feedback control. To this end, we apply recent advances in nonlinear control, to propose a systematic procedure to the problems of gait synthesis and control design. The core of the method lays on a nontrivial coordinate transformation, in order to approach the problem in a state-dependent form. For gait synthesis, such procedure allows a reduction of the search space, with the feasibility of considering energetic performance for optimization. For control design, this allows to apply concepts of transverse linearization, to design a nonlinear feedback control law, which performance is studied by numerical simulations.

We present results of modeling dynamics of a forestry manipulator, in which we consider its mechanics, as well as its hydraulic actuation system. The mathematical model of its mechanics is formulated by Euler-Lagrange equations, for which the addition of friction forces is straightforward. Dynamics of the hydraulic system is modeled upon first principle laws, which concern flow through orifices and fluid compressibility. These models lead to a set of equations with various unknown parameters, which are related to the inertias, masses, location of center of masses, friction forces, and valve coefficients. The numerical values of these parameters are estimated by the use of least-square methods, which is made feasible by transforming the models into linear representations. The results of simulation tests show a significant correspondence between measured and estimated variables, validating our modeling and identification approach.

A short term goal in the forest industry is semi-automation of existing machines for the tasks of logging and harvesting. One way to assist drivers is to provide a set of predefined trajectories that can be used repeatedly in the process. In recent years much effort has been directed to the design of control strategies and task planning as part of this solution. However, commercialization of such automatic schemes requires the installation of various sensing devices, computers and most of all a redesign of the machine itself, which is currently undesired by manufacturers. Here we present an approach of implementing predefined trajectories in an open-loop fashion, which avoids the complexity of sensor and computer integration. The experimental results are carried out on a commercial hydraulic crane to demonstrate that this solution is feasible in practice.

We consider a 3-link planar walker with two legs and an upper body. An actuator is introduced between the legs, and the torso is kept upright by torsional springs. The model is a 3-DOF impulsive mechanical system, and the aim is to induce stable limit-cycle walking in level ground. To solve the problem, the ideas of the virtual holonomic constraints approach are explored, used and extended. The contribution is a novel systematic motion planning procedure for solving the problem of gait synthesis, which is challenging for non-feedback linearizable mechanical systems with two or more passive degrees of freedom. For a preplanned gait we compute an impulsive linear system that approximates dynamics transversal to the periodic solution. This linear system is used for the design of a stabilizing feedback controller. Results of numerical simulations are presented to illustrate the performance of the closed loop system.

In the forest industry, trees are logged and harvested by human-operated hydraulic manipulators. Eventually, these tasks are expected to be automated with optimal performance. However, with todays technology the main problem is implementation. While prototypes may have rich sensing information, real cranes lack certain sensing devices, such as encoders for position sensing. Automating these machines requires unconventional solutions. In this paper, we consider the motion planning problem, which involves a redesign of optimal trajectories, so that open loop control strategies can be applied using feed-forward control signals whenever sensing information is not available.

The steps for modeling and control of a hydraulic rotary actuator are discussed. Our aim is to present experimental results working with a particular sensing device for angular position as a complement to pressure sensing devices. We provide the steps in experimental system identification used for modeling the system dynamics. The cascade controller designed contains an inner loop for an accurate tracking of torque while stabilizing position reference trajectories. The performance of this design is experimentally verified.

The problem of swinging up inverted pendulums has often been solved by stabilization of a particular class of homoclinic structures present in the dynamics of the standard pendulum. In this article new arguments are suggested to show how different homoclinic curves can be preplanned for dynamics of the passive-link of the robot. This is done by reparameterizing the motion according to geometrical relations among the generalized coordinates. It is also shown that under certain conditions there exist periodic solutions surrounding such homoclinic orbits. These trajectories admit designing feedback controllers to ensure exponential orbital stabilization. The method is illustrated by simulations and supported by experimental studies.

We consider trajectory planning for kinematically redundant manipulators used on forestry machines. The analysis of recorded data from human operation reveals that the driver does not use the full potential of the machine due to the complexity of the manipulation task. We suggest an optimization procedure that takes advantage of the kinematic redundancy so that time-efficient joint and velocity profiles along the path can be obtained. Differential constraints imposed by the manipulator dynamics are accounted for by employing a phase-plane technique for admissible path timings. Velocity constraints of the individual joints are particularly restrictive in hydraulic manipulators. Our study aims for semi-autonomous schemes that can provide assistance to the operator for executing global motions.

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.