Physical Human-Robot Interaction Control of an Upper Limb Exoskeleton with a Decentralized Neuro-Adaptive Control Scheme

Within the concept of physical human-robot interaction (pHRI), the most important criterion is the safety of the human operator interacting with a high degree of freedom (DoF) robot. Therefore, a robust control scheme is in high demand to establish safe pHRI and stabilize nonlinear, high DoF systems. In this paper, an adaptive decentralized control strategy is designed to accomplish the abovementioned objectives. To do so, a human upper limb model and an exoskeleton model are decentralized and augmented at the subsystem level to enable a decentralized control action design. Moreover, human exogenous force (HEF) that can resist exoskeleton motion is estimated using radial basis function neural networks (RBFNNs). Estimating both human upper limb and robot rigid body parameters, along with HEF estimation, makes the controller adaptable to different operators, ensuring their physical safety. The barrier Lyapunov function (BLF) is employed to guarantee that the robot can operate in a safe workspace while ensuring stability by adjusting the control law. Unknown actuator uncertainty and constraints are also considered in this study to ensure a smooth and safe pHRI. Then, the asymptotic stability of the whole system is established by means of the virtual stability concept and virtual power flows (VPFs) under the proposed robust controller. The experimental results are presented and compared to proportional-derivative (PD) and proportional-integral-derivative (PID) controllers. To show the robustness of the designed controller and its good performance, experiments are performed at different velocities, with different human users, and in the presence of unknown disturbances. The proposed controller showed perfect performance in controlling the robot, whereas PD and PID controllers could not even ensure stable motion in the wrist joints of the robot

Decentralized Nonlinear Control of Redundant Upper Limb Exoskeleton with Natural Adaptation Law

The aim of this work is to utilize an adaptive decentralized control method called virtual decomposition control (VDC) to control the orientation and position of the end-effector of a 7 degrees of freedom (DoF) right-hand upper-limb exoskeleton. The prevailing adaptive VDC approach requires tuning of 13n adaptation gains along with 26n upper and lower parameter bounds, where n is the number of rigid bodies. Therefore, utilizing the VDC scheme to control high DoF robots like the 7-DoF upper-limb exoskeleton can be an arduous task. In this paper, a new adaptation function, so-called natural adaptation law (NAL), is employed to eliminate these burdens from VDC, which results in reducing all 13n gains to one and removing dependency on upper and lower bounds. In doing so, VDC-based dynamic equations are restructured, and inertial parameter vectors are made compatible with NAL. Then, the NAL adaptation function is exploited to design a new adaptive VDC scheme. This novel adaptive VDC approach ensures physical consistency conditions for estimated parameters with no need for upper and lower bounds. Finally, the asymptotic stability of the algorithm is proved with the virtual stability concept and the accompanying function. The experimental results are utilized to demonstrate the excellent performance of the proposed new adaptive VDC scheme.Comment: Manuscript is published in 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids

Hybrid Controller for Robot Manipulators in Task-Space with Visual-Inertial Feedback

This paper presents a visual-inertial-based control strategy to address the task space control problem of robot manipulators. To this end, an observer-based hybrid controller is employed to control end-effector motion. In addition, a hybrid observer is introduced for a visual-inertial navigation system to close the control loop directly at the Cartesian space by estimating the end-effector pose. Accordingly, the robot tip is equipped with an inertial measurement unit (IMU) and a stereo camera to provide task-space feedback information for the proposed observer. It is demonstrated through the Lyapunov stability theorem that the resulting closed-loop system under the proposed observer-based controller is globally asymptotically stable. Besides this notable merit (global asymptotic stability), the proposed control method eliminates the need to compute inverse kinematics and increases trajectory tracking accuracy in task-space. The effectiveness and accuracy of the proposed control scheme are evaluated through computer simulations, where the proposed control structure is applied to a 6 degrees-of-freedom long-reach hydraulic robot manipulator

A Global Asymptotic Convergent Observer for SLAM

This paper examines the global convergence problem of SLAM algorithms, an issue that faces topological obstructions. This is because the state-space of attitude dynamics is defined on a non-contractible manifold: the special orthogonal group of order three SO(3). Therefore, this paper presents a novel, gradient-based hybrid observer to overcome these topological obstacles. The Lyapunov stability theorem is used to prove the globally asymptotic convergence of the proposed algorithm. Finally, comparative analyses of two simulations were conducted to evaluate the performance of the proposed scheme and to demonstrate the superiority of the proposed hybrid observer to a smooth observer.Comment: 7 pages, 8 figures, conferenc

Harvester Boom Tip Acceleration Control During a Crosscutting - Theoretical Background

The cutting function is an essential part of a harvester's work in the cut-to-length method. The quality of cutting is the most significant feature of a cut. Trees should be cut without causing damage to logs produced. Nowadays end checks of logs are the main problem in the cutting process. It has been observed that end checks are found in as many as 70% of the logs produced by harvesters. Cutting damage reduces the amount of useful material and causes considerable economical loss to the sawmill and veneer industries. This study presents a theoretical background for the boom-lowering function, which is one solution to avoid cutting damage during the timber cutting process. The purpose is to momentarily counterbalance the gravitational force of the log in horizontal timber cutting. The study discusses the feasibility of controlling the boom tip in the vertical plane during the cut. In this study the boom tip motion trajectory along the g-vector is modelled for both one and two linear actuators. On the basis of this theoretical study, it seems that acceleration of one g is possible to realise with certain improvements in hydraulics. However, experimental measurements are required to verify these theoretical results. This will include the more detailed study of the effects of deceleration limits on boom stability

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Path Planning and Smoothing for 4WDs Hydraulic Heavy-Duty Field Robots

This paper discusses the path planning and path-following control for a four wheel drive (4WD), steer-articulated boom lift driven by hydraulic actuators. The environment is assumed to be both static and known. The path planning will be done in two phases, where the first one finds a crude, collision-free path accounting for the vehicle dimensions, and this path will be smoothed with a path smoothing algorithm to satisfy the kinematic and dynamic constraints imposed by the vehicle and its actuators. The path smoothing algorithm will be chosen from several candidates by using a simulated test scenario. Then, the simulation results will be used to verify the path planners feasibility in heavy-duty, four-wheel-steered field robots having hydraulic actuators and high inertia.publishedVersionPeer reviewe

Flow-Bounded Velocity Controller for Hydraulic Bulldozers

The bulldozer is a mobile earthmoving machine with a differentially steered mobile base and an onboard manipulator used for soil cutting and transportation. Grading the ground to match a desired contour is an end-effector path-following task, with required joint rates dependent on mobile base motion. The offline planning of travel velocity profiles that respect the available hydraulic flowrate limits is difficult due to uncertainties in the machine–soil interactions. Hence, we propose a flow-bounded velocity controller enabling accurate automatic grading with online velocity scaling. The capacity of hydrostatic transmission and manipulator actuators, as well as the desired velocity, are considered when deciding the commanded velocity reference for the mobile base. Our dynamic simulation results show that, with the proposed controller, a desired ground profile is cut accurately when the machine operates at its performance limits. Comparison to constant velocity driving shows that errors in blade positioning are reduced dramatically. Constant velocity selected to keep the flow within limits results in longer completion times compared to our solution, making it more time optimal. Furthermore, the rpm of the diesel engine can be reduced to save fuel without compromising control performance.publishedVersionPeer reviewe