Correction: Diagrammatic physical robot models

The safety of human-collaborative operations with robots depends on monitoring the external torque of the robot, in which there are toque sensor-based and torque sensor-free methods. Economically, the classic method for estimating joint external torque is the first-order momentum observer (MOB) based on a physic model without torque sensors. However, uncertainties in the dynamic model, which encompasses parameters identification error and joint friction, affect the torque estimation accuracy. To address this issue, this paper proposes using the backpropagation neural network (BPNN) method to estimate joint external torque without the delicate physical model by utilizing the powerful machine learning ability to handle the uncertainties of the MOB method and improve the accuracy of torque estimation. Using data obtained from the torque sensor to train the BPNN to build up a digital torque model, the trained BPNN can perceive force in practical applications without relying on the torque sensor. In the end, by contrast to the classic first-order MOB, the result demonstrates that BPNN achieves higher estimation accuracy compared to the MOB.

Increasing amounts of robotics applications and possible job opportunities in the industry within the robotics field encourage more universities to involve robotics subject in their current programs or incorporate robotics engineering as a new department. This highlights the importance of comprehensible robotics teaching for more people with various levels of technical background. One of the major subjects at the university level in robotics education is representing the physical robot model using mathematical notations. The majority of the current teaching methods of robotics theory for undergraduate students use conventional approaches from robotics books which relies on 3D pictures and sketches for illustration. There are a few modern approaches where the book chapters are linked to supplemental videos, however, the lack of interaction diminishes the student engagement. Moreover, there are some simulators to enhance visual and interactive skills, but they are either costly or robot specific and require adequate competence of programming skills on the associated programming language. In this paper, a serious game to be used in robotics teaching for bachelor students with various technical backgrounds is presented. The game combines the traditional notations in robot modelling with a gamified approach so that the students can comprehend and imagine easier.

In this study, a graphic simulator that is used to simulate problems related to kinematics and dynamics for an exoskeleton robot arm with 5 degrees of freedom (DoF) was presented. The graphic simulator utilized the advantages of design software SolidWorks, Catia, and the computing and simulation power of SimMechanics Toolbox in Matlab. The core of the proposed graphic simulator is algorithm to solve the kinematics and dynamic problems of a developing upper-limb rehabilitation robot. The study used the proposed optimization-based algorithm to solve the inverse kinematics (IK) problem for the redundant robot model. Endpoint trajectories were imported from measurement data. The joints variable solutions obtained before entering the dynamics problem were smoothed to ensure feasibility in the later calculation process. A process to solve the inverse dynamics problem using physical model by combining the power of two software SolidWorks and SimMechanics was also proposed. This process ensured that the Robot’s design could be changed and updated to the kinematics calculation fast and easily. To evaluate this procedure, we also compared these dynamics results with results when applying the Lagrange–Euler formulation. All these calculation and simulation processes have been integrated into the graphic simulator software to show efficiency and user-friendliness.

Fishes that use undulatory locomotion occasionally change their inherent kinematics in terms of some natural behavior. This special locomotion pattern was vividly dubbed “hybrid kinematics” by biologists recently. In this paper, we employed a physical model with body shape of a Mackerel (Scomber scombrus), to use the three most typical undulatory kinematics: anguillform, carangiform and thunniform, to investigate the hydrodynamic performance of the so-called “hybrid kinematics” biological issue. Theoretical models of both kinematics and hydrodynamics of the physical model swimming were developed. Base on this model, the instantaneous force produced by fish undulatory body and flapping tail were calculated separately. We also quantitatively measured the hydrodynamic variables of the robotic model swimming with the three undulatory kinematics on an experimental apparatus. The results of both theoretical model and experiment showed that the robot with thunniform kinematics not only reaches a higher speed but also is more efficient during steady swimming mode. However, anguilliform kinematics won the speed race during the initial acceleration. Additionally, the digital particle image velocimetry (DPIV) results showed some difference of the wake flow generated by the robotic swimmer among the three undulatory kinematics. Our findings may possibly shed light on the motion control of a biomimetic robotic fish and provide certain evidence of why the “hybrid kinematics” exists within the typical undulatory locomotion patterns.

This paper focuses on developing a virtually controlled robot by integrating Virtual Reality (VR) and Robot Operating System (ROS). Robots can be used in certain environments where humans cannot be physically present to undertake a task. To increase the safety of humans, controlling a robot virtually is one of the best solutions. This paper shows how the VR-controlled manipulator will help in different fields like hazardous environments, underwater research, and the medical field for surgical operations. Unity 3D is used to develop the virtual environment, and ROS is used for communication with the physical robot. A Virtual environment would be developed where an exact robot (URDF) model can be designed. The interaction with the virtual environment is done with the help of VR headsets and controllers. ROS acts as the communication bridge between virtual and physical robots. A prototype has been developed to be controlled through virtual controllers that can interact through ROS.

A tendon-driven multijoint robot is a humanlike robot which is driven by a tendon-driven actuator. One of the problems is that the complexity of the tendon-driven multijoint robot body structure. The complexity makes it difficult to control body by commonly used methods which are based on a dynamics computation of a physical robot model. We proposed a appropriate control method for tendon-driven actuators. In this control method, we defined an ideal reaction model that is based on a physical motion equation. This equation includes an elastic term, inertia term and a friction term. The control method then calculates target rotational velocity of the actuator from the motion equation. Finally, the motor driver of the actuator outputs voltage to follow the target velocity through a basic PID control. Our control method enables the tendon-driven actuator to act as a mechanical spring. Through this, the tendon-driven multijoint robot can attain the flexibility to adapt to external forces applied by collision with objects without using a precise dynamics computation. Moreover, our control method enables the tendon-driven multijoint robot to adjust its stiffness and flexibility depending on the purpose of its given tasks. We tested this control method by using KOJIRO, and showed the control method works as declared.

In order to realize the collaborative operation between the physical prototype and the virtual prototype of industrial robot, a digital twin model of a six-degree-of-freedom industrial robot was established. The structure and motion parameters of the 6-DOF industrial robot are introduced. The virtual prototype model of the industrial robot was established based on Visual One; the digital twin modeling of the industrial robot was completed by the three methods communication between the virtual prototype of the industrial robot and the physical prototype was realized, and the virtual and real collaborative operation of the twin robot and the physical robot was realized. Experiments show that when manipulating the movement of the robot on the physical terminal, the digital twin was consistent with its behavior. The research results provide references for the application of digital twin technology in the field of industrial robots.

It has long been established that simple springmass models can accurately represent the dynamics of legged locomotion.Existing work in this domain, however, almost exclusively focuses on the idealized Spring-Loaded Inverted Pendulum (SLIP) model and neglects passive dissipative effects unavoidable in any physical robot or animal.In this paper, we extend on a recently proposed analytic approximation to the stance trajectories of a dissipative SLIP model to analyze stability properties of a planar hopper with a single rotary actuator at the hip.We first describe how a suitably chosen torque controller can compensate for damping losses, maintaining the same energy level across strides and hence reducing the return map to a single dimension.We then identify and characterize equilibrium points for this return map under a fixed leg placement policy and show that "uncontrolled" asymptotic stability is feasible for this energy-regulated system.Subsequent presentation of simulation evidence establishes that the predictions of this approximate model are consistent with the exact plant model.The paper concludes with the application of our energy-regulation scheme to the design of a task-level gait controller that uses explicit leg placement commands in conjunction with the hip torque.

Digital twin-based industrial cloud robotics: Framework, control approach and implementation

This paper deals with modeling of a novel spherical robot using bond graph approach, in which a hydraulic driver mechanism is deployed. The proposed method is used to describe the dynamics of the system in various physical domains. The Newton-Euler formalism with body fixed coordinates is exploited in order to model the dynamics of the proposed spherical robot. Ground interaction as Coulomb friction is considered. Simulation results are obtained for equal inputs in open-loop physical model.

Based on the principle of bionic hexapod, a 3D virtual prototype model of the bionic hexapod robot and the contact model between its feet and the ground are established by using MSC. ADAMS mechanical dynamics software to study the motion of the bionic hexapod robot on the horizontal ground. And then, the kinematics analysis of a single leg of the robot is made to realize the overall motion control of the robot. This paper analyzes the gait principle of the bionic hexapod robot and introduces the gait of the robot used. By simulating the straight motion of the robot, the angular velocity and angular acceleration in the legs of the virtual prototype model are obtained. The study is a theoretical foundation for the design of the physical model and motion planning of a bionic hexapod robot.

Robot learning with GA-based fuzzy reinforcement learning agents

Ribbon-fin-based propulsion has rich locomotor capabilities that can enhance the mobility and performance of underwater vehicles navigating in complex environments. Bony fishes using this type of propulsion send one or multiple traveling waves along an elongated fin with the actuation of highly flexible rays that are interconnected by an elastic membrane. In this work, we study how the use of flexible rays and different morphology can affect the performance of ribbon-fin propulsion. We developed a physical model composed of 15 rays that are interconnected with an elastic membrane. We tested four different ray flexural stiffness and four aspect ratios. The robotic model was tested in a low-turbulence flume under two flow conditions ([Formula: see text] wavelength/s). In two experimental sets, we measured fin kinematics, net surge forces, and power consumption. Using these data, we perform a thrust and power analysis of the undulating fin. We present the thrust coefficient, power coefficient, and propulsive efficiency. We find that the thrust generation was linear with the enclosed area swept by the fin, and square of the relative velocity between the incoming flow and traveling wave. The thrust coefficient levels off around 0.5. In addition, for our parameter range, we find that the power consumption scales by the cube of the effective tangential velocity of the rays [Formula: see text] (A is the amplitude of the ray oscillating motion, and [Formula: see text] is the angular velocity). We show that a decay in stiffness decreases both thrust production and power consumption. However, for rays with high flexural stiffness, the difference in thrust compared with rigid rays is minimal. Moreover, our results show that flexible rays can improve the propulsive efficiency compared with a rigid counterpart. Finally, we find that the morphology of ribbon fin affects its propulsive efficiency. For the aspect ratio considered in our experiments, [Formula: see text] was the most efficient compared with [Formula: see text]. Our results suggest that there could be an optimal morphology for a given ribbon fin kinematics. Therefore, both natural swimmers and underwater vehicles using ribbon-fin-based propulsion can take advantage of flexible rays and optimal aspect ratio to improve propulsive performance.

Versions of the proportional-integral-derivative (PID) controllers are most widespread type of controllers used to control plants, in achieving satisfactory performance. Versions of PID controller are also used for controlling robotic plants. With increased speed of operation and more stringent performance requirements PID controller alone will not suffice. Control performance improve significantly by adding second controller that computes necessary driving torque from current operating condition, based on robot model. Two types of cerebellum based controllers where tested in acquiring robot model. First one is standard Albus cerebellar model articulation controller (CMAC), and second one is new cerebellar model controller with added functionality for some of cerebellar neuron types, namely Golgi cell, basket cell, and stellate cell (CMACgbs). Physical modeling of robot joint with SimMechanics was used as testing plant for rapid prototyping. Cerebellar controller features addressed are size of the neural network, learning process, and generalization.

With the increasing complexity of control systems in industrial process control, traditional controllers are greatly limited in many occasions, so the development of new controller is extremely urgent. This paper combines adaptive feedback control with PID control, and designs a new type of adaptive PID feedback controller. The designed controller is verified by establishing a physical model of the 6-DOF collaborative robot. On the basis of improved adaptive PID feedback control, precise tracking control of multi-DOF cooperative robots is achieved, which improves response speed and eliminates steady-state errors. The designed controller is compared with classical PID control and adaptive control. The steady-state performance, dynamic performance, and anti-interference performance of position control and velocity control are analyzed. The improved adaptive PID feedback control has better control performance. The feasibility and reliability of the adaptive PID feedback controller for collaborative robots are verified.