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Manipulators are often subjected to joint flexibility caused by various causes in industrial applications, such as shaft windup, harmonic drives and bearing deformation. However, many industrial robots are only equipped with motor-side encoders because link-side encoders and torque transducers are expensive. Because of joint flexibility and resulted slow response rate, control performance of these manipulators is very limited. Based on this, the purpose of this paper is to use easy-to-install and cheap accelerometers to improve control performance of such manipulators.

First, a novel tip-acceleration feedback method is proposed to avoid amplifications of approximation errors caused by inversion of the Jacobian matrix. Then, a new control scheme, consisting an artificial neural network, a proportional-derivative (PD) controller and a reference model, is proposed to track motor-side position and suppress link-side vibration.

By using the proposed tip-acceleration feedback method, each link’s vibration can be suppressed correlatively. Through the networks, smaller motor-side tracking errors can be obtained and unknown dynamics can be compensated. Tracking and convergence performance of the network-based system can be improved by using the additional PD controller.

The originality is based on using accelerometers to improve link-side vibration suppression and control performance of flexible-joint manipulators. The previously used methods need expensive link-side sensors or accurate robot model, which is unavailable for many industrial robots only equipped with motor-side encoders. The report proposed a novel acceleration feedback method and used networks to solve such problems.

The safety performance of cooperative robots is particularly important. This paper aims to study collision detection and response of cooperative robots, which meet the lightweight requirements of cooperative robots and help to ensure the safety of humans and robots.

This paper proposes a collision detection, recognition and response method based on dynamic models. First, this paper identifies the dynamic model of the robot. Second, an external torque observer is established based on the model, and a dynamic threshold collision detection method is designed to reduce the interference of model uncertainty on collision detection. Finally, a collision position and direction estimation method is designed, and a robot collision response strategy is proposed to reduce the harm caused by collisions to humans.

Comparative experiments are conducted on static threshold and dynamic threshold collision detection, and the results showed that the static threshold only detected one collision while the dynamic threshold could detect all collisions. Conducting collision position and direction estimation and collision response experiments, and the results show that this method can determine the location and direction of collision occurrence, and enable the robot to achieve collision separation.

This paper designs a dynamic threshold collision detection method that does not require external sensors. Compared with static threshold collision detection methods, this method can significantly improve the sensitivity of collision detection. This paper also proposes a collision position direction estimation method and collision separation response strategy, which can enable robots to achieve post collision separation and improve the safety of cooperative robots.

The purpose of the paper is to propose an efficient and accurate force/torque (F/T) sensing method for the robotic wrist-mounted six-dimensional F/T sensor based on an excitation trajectory.

This paper presents an efficient and accurate F/T sensing method based on an excitation trajectory. First, the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity. Therefore, the sensing accuracy is improved. Then, the excitation trajectory with optimized poses is used for robot following and data acquisition. The data acquisition is not limited by poses and its time can be significantly shortened. Finally, the least squares method is used to identify parameters and sense contact forces/torques.

Experiments have been carried out on the self-developed robot manipulator. The results strongly demonstrate that the proposed approach is more efficient and accurate than the existing widely-adopted method. Furthermore, the data acquisition time can be shortened from more than 60 s to 3 s/20 s. Thus, the proposed approach is effective and suitable for fast-paced industrial applications.

The main contributions of this paper are as follows: the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity; and the excitation trajectory with optimized poses is used for robot following and data acquisition.

Most manufacturing plants choose the easy way of completely separating human operators from robots to prevent accidents, but as a result, it dramatically affects the overall quality and speed that is expected from human–robot collaboration. It is not an easy task to ensure human safety when he/she has entered a robot’s workspace, and the unstructured nature of those working environments makes it even harder. The purpose of this paper is to propose a real-time robot collision avoidance method to alleviate this problem.

In this paper, a model is trained to learn the direct control commands from the raw depth images through self-supervised reinforcement learning algorithm. To reduce the effect of sample inefficiency and safety during initial training, a virtual reality platform is used to simulate a natural working environment and generate obstacle avoidance data for training. To ensure a smooth transfer to a real robot, the automatic domain randomization technique is used to generate randomly distributed environmental parameters through the obstacle avoidance simulation of virtual robots in the virtual environment, contributing to better performance in the natural environment.

The method has been tested in both simulations with a real UR3 robot for several practical applications. The results of this paper indicate that the proposed approach can effectively make the robot safety-aware and learn how to divert its trajectory to avoid accidents with humans within the workspace.

The method has been tested in both simulations with a real UR3 robot in several practical applications. The results indicate that the proposed approach can effectively make the robot be aware of safety and learn how to change its trajectory to avoid accidents with persons within the workspace.

This paper provides a novel collision avoidance framework that allows robots to work alongside human operators in unstructured and complex environments. The method uses end-to-end policy training to directly extract the optimal path from the visual inputs for the scene.

Several studies have aimed to develop robotic systems which move in transmission lines. Until this moment, all of them have a high weight and cost associated with the equipment and reduced battery autonomy time. In this context, this paper aims to propose the POLIBOT (POwer Lines Inspection roBOT) with low cost and weight, enabling the movement over the lines and an easier installation and remove.

The designed robot uses the Profiles Manufacturing Methodology (PMM). The construction of the robot mechanical structure uses modularized aluminum parts built through square profiles. Thus, it’s possible a drastic reduction in production time as well as cost reduction and weight when comparing this method with other manufacturing processes like foundry, for example. For hardware and software systems, the use of free and open source software causes a significant reduction in cost and project execution time. The benefits of using open source systems are immeasurable, both from academic and industrial applications.

The POLIBOT platform is one solution to the problem of inspection in power lines. With this robot, more lines are maintained with lower time. In its constructive aspect, the robotic mechanism is designed using principles of bioengineering. The use of this principle was successful, considering that obstacle transposition is performed with stability and low energy consumption.

The suggestion for future researches is to replace the battery for solar energy and construction in polymeric material to avoid high magnetic fields.

The commercial application is evident because manual inspections are inefficient, very expensive and dangerous. Thus, it is growing the number of researches that develop mechatronics systems for this kind of inspection.

The impact is the reduction of accidents because the present procedure requires precision of movements, where the pilot and electrical technician are close to high electrical and magnetic fields. In addition, for some tasks, the worker has to walk on the line to reach some important points. Thus, those tasks involve high risk of death.

The PMM methodology represents an innovation to the state of the art because others robotic mechanisms proposed for inspection tasks present total structure mass between 50 and 100 kg and POLIBOT has only 9 kg. Other fact is its price for implementation as this robot used the robot operating system (ROS) framework, what dispense the use of licenses. Other important features are that the robot performs the tasks autonomously, which reduces errors introduced by the operator and its low manufacturing cost as compared with other projects.

This paper aims to deal with the problem of programming robots in industrial contexts, where the need of easy programming is increasing, while robustness and safety remain fundamental aspects.

A novel approach of robot programming can be identified with the manual guidance that permits to the operator to freely move the robot through its task; the task can then be taught using Programming by Demonstration methods or simple reproduction.

In this work, the different ways to achieve manual guidance are discussed and an implementation using a force/torque sensor is provided. Experimental results and a use case are also presented.

The use case shows how this methodology can be used with an industrial robot. An implementation in industrial contexts should be adjusted accordingly to ISO safety standards as described in the paper.

This paper presents a complete state-of-the-art of the problem and shows a real practical use case where the approach presented could be used to speed up the teaching process.

Soft robotics is currently a rapidly growing new field of robotics whereby the robots are fundamentally soft and elastically deformable. Fabrication of soft robots is currently challenging and highly time- and labor-intensive. Recent advancements in three-dimensional (3D) printing of soft materials and multi-materials have become the key to enable direct manufacturing of soft robots with sophisticated designs and functions. Hence, this paper aims to review the current 3D printing processes and materials for soft robotics applications, as well as the potentials of 3D printing technologies on 3D printed soft robotics.

The paper reviews the polymer 3D printing techniques and materials that have been used for the development of soft robotics. Current challenges to adopting 3D printing for soft robotics are also discussed. Next, the potentials of 3D printing technologies and the future outlooks of 3D printed soft robotics are presented.

This paper reviews five different 3D printing techniques and commonly used materials. The advantages and disadvantages of each technique for the soft robotic application are evaluated. The typical designs and geometries used by each technique are also summarized. There is an increasing trend of printing shape memory polymers, as well as multiple materials simultaneously using direct ink writing and material jetting techniques to produce robotics with varying stiffness values that range from intrinsically soft and highly compliant to rigid polymers. Although the recent work is done is still limited to experimentation and prototyping of 3D printed soft robotics, additive manufacturing could ultimately be used for the end-use and production of soft robotics.

The paper provides the current trend of how 3D printing techniques and materials are used particularly in the soft robotics application. The potentials of 3D printing technology on the soft robotic applications and the future outlooks of 3D printed soft robotics are also presented.

The purpose of this paper is to present experience from a real‐world demonstration of autonomous industrial mobile manipulation (AIMM) based on the mobile manipulator “Little Helper” performing multiple part feeding at the pump manufacturer Grundfos A/S.

The necessary AIMM technologies exist at a mature level – the reason that no mobile manipulators have yet been implemented in industrial environments, is that research in the right applications have not been carried out. The paper proposes a pragmatic approach consisting of: a commercial‐off‐the‐shelf (COTS) mobile manipulator system design (“Little Helper”), a suitable and comprehensive industrial application (multiple part feeding), and a general implementation concept for industrial environments (the “Bartender Concept”).

Results from the three days of real‐world demonstration show that “Little Helper” is capable of successfully servicing four part feeders in three production cells using command signals from an Open Process Control (OPC) server. Furthermore, the paper presents future research and development suggestions for AIMM, which contributes to near‐term industrial maturation and implementation.

The paper presents a full‐scale demonstration of a state‐of‐the‐art COTS autonomous mobile manipulator system with particular focus on industrial utilization and application.

This paper aims to present an adaptive fuzzy sliding mode controller with nonlinear observer (AFSMCO) for the redundant robotic manipulator handling a varying payload to achieve a precise trajectory tracking in the task space. This approach could be applied to solve the problems caused by the dynamic effect of the varying payload to robotic system caused by model uncertainties.

First, a suitable observer using the recursive algorithm is presented for an accurate estimation of external disturbances caused by a variable payload. Second, the adaptive fuzzy logic is designed to approximate the parameters of the sliding mode controller combined with nonlinear observer (SMCO) to avoid chattering in real time. Moreover, Lyapunov theory is applied to guarantee the stability of the proposed closed-loop robotic system. Finally, the effectiveness of the proposed control approach and theoretical discussion are proved by simulation results on a seven-link robot and demonstrated by a humanoid robot platform.

The varying payload leads to large variations in the dynamics of the manipulator and the tracking error. To achieve high-precision position tracking, nonlinear observer was introduced to feed into the sliding mode control (SMC) which had improved the ability to resist the external disturbance. In addition, the chattering caused by the SMC was eliminated by recursively approximating the switching gain with the usage of adaptive fuzzy logic. Therefore, a distributed control strategy solves the problems of an SMC implementation in improving its tracking performance and eliminating the chattering of the system control.

The AFSMCO is proposed for the first time and used to control the redundant robotic manipulator that handles the varying payload. The proposed control algorithm possesses better robustness and higher precision for the trajectory tracking than classical SMC.

This paper aims to develop a climbing robot to help people inspect lamps of high-mast lighting.

The robot consists of driving mechanism, suspension mechanism and compression mechanism. The driving mechanism is realized by link chains and sprockets, which are arranged opposite to each other, to form a dual caterpillar mechanism. The compression mechanism squeezes the caterpillar, and rubber feet “grasps” the steel rope to generate enough adhesion forces. The suspension mechanism is used to compensate the contraction or extension of the chains. The robot is equipped with a DC motor with a rated power of 250 W and a wireless module to communicate with the operator’s console. The dynamic model of the robot and the control strategy is derived, and the stability of the controller is proofed.

The payload experiment shows the robot can afford up to 3.7 times payload versus its own weight. Even when the payload is 30 kg, the robot can maintain a speed of the 1 m/s. The experiments also show that the tracking error of the robot reaches zero.

The proposed moving mechanism has a high load/weight ratio, which is a verified solution for the cable inspection purpose.

A rope climbing robot for high mast lighting inspection is proposed. The developed mechanism can reach a speed of 1 m/s with the payload of 30 kg, while its own weight is only 15.6 kg. The payload/weight ratio of the robot is 2.24; this value is rather good in many climbing robots reported in other renowned journal.