Robotics

Water ingression is a critical issue in honeycomb composite structures, which could result in catastrophic structural failure. In the aviation industry, they are widely used to manufacture critical aircraft structural components including fuselage, wings, and flight control surfaces. Catastrophic failure of these structures would be disastrous, thus identifying water accumulation in earlier stages of the defect is necessary. The conventional non-destructive testing method is thermography which is performed using handheld thermography cameras by manually accessing the specific areas. This method of inspection has been identified to be a risky, costly, time-consuming, and inspector-dependent technique. This paper describes using a wall-climbing robotic platform that can be controlled remotely to access and perform the inspection on a targeted structural area replacing the manual process. The designed wall-climbing inspection robot onboard a heat pump to stimulate the composite surface to an adequate temperature and, an infrared sensor to feed the real-time temperature data via Bluetooth serial communication to a remote computer system to be processed into a thermal image and evaluated to determine the presence of water. The results obtained from the thermographic sensor are validated with the comparison of the Fluke thermography camera. Full article

Bionic hands have been employed in a wide range of applications, including prosthetics, robotic grasping, and human–robot interaction. However, considering the underactuated and nonlinear characteristics, as well as the mechanical structure’s backlash, achieving natural and intuitive teleoperation control of an underactuated bionic hand remains a critical issue. In this paper, the teleoperation control of an underactuated bionic hand using wearable and vision-tracking system-based methods is investigated. Firstly, the nonlinear behaviour of the bionic hand is observed and the kinematics model is formulated. Then, the wearable-glove-based and the vision-tracking-based teleoperation control frameworks are implemented, respectively. Furthermore, experiments are conducted to demonstrate the feasibility and performance of these two methods in terms of accuracy in both static and dynamic scenarios. Finally, a user study and demonstration experiments are conducted to verify the performance of these two approaches in grasp tasks. Both developed systems proved to be exploitable in both powered and precise grasp tasks using the underactuated bionic hand, with a success rate of $98.6\%$ and $96.5\%$, respectively. The glove-based method turned out to be more accurate and better performing than the vision-based one, but also less comfortable, requiring greater effort by the user. By further incorporating a robot manipulator, the system can be utilised to perform grasp, delivery, or handover tasks in daily, risky, and infectious scenarios. Full article

Among the tilt-rotors (quadrotors) developed in recent decades, Ryll’s model with eight inputs (four magnitudes of thrusts and four tilting angles) attracted great attention. Typical feedback linearization maneuvers all of the eight inputs with a united control rule to stabilize this tilt-rotor. Instead of assigning the tilting angles by the control rule, the recent research predetermines the tilting angles and leaves the magnitudes of thrusts with the only control signals. These tilting angles are designed to mimic the cat-trot gait while avoiding the singular decoupling matrix in feedback linearization. To complete the discussions of the cat-gait inspired tilt-rotor gaits, this research addresses the analyses on the rest of the common cat gaits, walk, run, transverse gallop, and rotary gallop. It is found that the singular decoupling matrix exists in walk gait, transverse gallop gait, and rotary gallop gait; the decoupling matrix can hardly be guaranteed to be invertible analytically. Further modifications (scaling) are conducted to these three gaits to accommodate the application of feedback linearization; the acceptable attitudes, leading to invertible decoupling matrix, for each scaled gait are evaluated in the roll-pitch diagram. The modified gaits with different periods are then applied to the tilt-rotor in tracking experiments, in which the references are uniform rectilinear motion and uniform circular motion with or without the equipment of the modified attitude-position decoupler. All the experiments are simulated in Simulink, MATLAB. The result shows that these gaits, after modifications, are feasible in tracking references, especially for the cases equipped with the modified attitude-position decoupler. Full article

In environments shared with humans, Autonomous Mobile Robots (AMRs) should be designed with human-aware motion-planning skills. Even when AMRs can effectively avoid humans, only a handful of studies have evaluated the human perception of mobile robots. To establish appropriate non-verbal communication, robot movement should be legible and should consider the human element. In this paper, a study that evaluates humans’ perceptions of different AMR courtesy behaviors at industrial facilities, particularly at crossing areas, is presented. To evaluate the proposed kinesic courtesy cues, we proposed five tests (four proposed cues—stop, deceleration, retreating, and retreating and moving aside—and one control test) with a set of participants taken two by two. We assessed three different metrics, namely, the participants’ self-reported trust in AMR behavior, the legibility of the courtesy cues in the participants’ opinions, and the behavioral analysis of the participants related to each courtesy cue tested. The retreating courtesy cue, regarding the legibility of the AMR behavior, and the decelerate courtesy cue, regarding the behavioral analysis of the participants’ signs of hesitation, are better perceived from the forward view. The results obtained regarding the participants’ self-reported trust showed no significant differences in the two participant perspectives. Full article

Soft and flexible strain sensors are becoming popular for many robotic applications. This article presents a stretchable capacitive sensor by combining a conductive filler of carbon black with elastomers and implementing shielding to reduce parasitic interference, applied to an underactuated robotic hand. Sensors with different configurations were explored. The results show that a shield introduced to the sensor does have some mitigation effect on external interference. Two sensor configurations were explored: longitudinal interdigitated capacitive (LIDC) sensor, where the interdigitated fingers lie along the same axis as the strain, and transverse interdigitated capacitive (TIDC) sensor, where the interdigitated fingers are orthogonal to the strain direction. The LIDC configuration had better performance than TIDC. The fabricated two-layered LIDC sensor had a gage factor of 0.15 pF/mm and the rates of capacitive creep of 0.000667 pF/s and 0.001 pF/s at loads of 120 g and 180 g, respectively. The LIDC sensors attached to an underactuated robotic hand demonstrate the sensors’ ability to determine the bending angles of the proximal interphalangeal (PIP) and metacarpophalangeal (MCP) joints. Full article

Although substantial advancements have been achieved in robot-assisted surgery, the blueprint to existing snake robotics predominantly focuses on the preliminary structural design, control, and human–robot interfaces, with features which have not been particularly explored in the literature. This paper aims to conduct a review of planning and operation concepts of hyper-redundant serpentine robots for surgical use, as well as any future challenges and solutions for better manipulation. Current researchers in the field of the manufacture and navigation of snake robots have faced issues, such as a low dexterity of the end-effectors around delicate organs, state estimation and the lack of depth perception on two-dimensional screens. A wide range of robots have been analysed, such as the i²Snake robot, inspiring the use of force and position feedback, visual servoing and augmented reality (AR). We present the types of actuation methods, robot kinematics, dynamics, sensing, and prospects of AR integration in snake robots, whilst addressing their shortcomings to facilitate the surgeon’s task. For a smoother gait control, validation and optimization algorithms such as deep learning databases are examined to mitigate redundancy in module linkage backlash and accidental self-collision. In essence, we aim to provide an outlook on robot configurations during motion by enhancing their material compositions within anatomical biocompatibility standards. Full article

Human–robot collaboration (HRC) enables humans and robots to coexist in the same working environment by performing production operations together. HRC systems are used in advanced manufacturing to improve the productivity and efficiency of a manufacturing process. The question is which HRC systems can ensure that humans can work with robots in a safe environment. This present study proposes a solution through the development of a low-cost sensory glove. This glove was developed using a number of hardware and software tools. The sensory glove analysed and computed the motion and orientation of a worker’s hand. This was carried out to operate the robot through commands and actions while under safe operating conditions. The sensory glove was built as a mechatronic device and was controlled by an algorithm that was designed and developed to compute the data and create a three-dimensional render of the glove as it moved. The image produced enabled the robot to recognize the worker’s hand when collaboration began. Tests were conducted to determine the accuracy, dynamic range and practicality of the system. The results showed that the sensory glove is an innovative low-cost solution for humans and robots to collaborate safely. The sensory glove was able to provide a safe working environment for humans and robots to collaborate on operations together. Full article

In this article, a soft robot arm that has the ability to twist in two directions is designed. This continuum arm is inspired by the twisting movements of the human upper limb. In this novel continuum arm, two contractor pneumatic muscle actuators (PMA) are used in parallel, and a self-bending contraction actuator (SBCA) is laid between them to establish the twisting movement. The proposed soft robot arm has additional features, such as the ability to contract and bend in multiple directions. The kinematics for the proposed arm is presented to describe the position of the distal end centre according to the dimensions and positions of the actuators and the bending angle of the SBCA in different pressurized conditions. Then, the rotation behaviour is controlled by a high precision controller system. Full article

In this paper, we present a quantitative performance investigation and repeatability assessment of a mobile robotic system for 3D mapping. With the aim of a more efficient and automatic data acquisition process with respect to well-established manual topographic operations, a 3D laser scanner coupled with an inertial measurement unit is installed on a mobile platform and used to perform a high-resolution mapping of the surrounding environment. Point clouds obtained with the use of a mobile robot are compared with those acquired with the device carried manually as well as with a terrestrial laser scanner survey that serves as a ground truth. Experimental results show that both mapping modes provide similar accuracy and repeatability, whereas the robotic system compares favorably with respect to the handheld modality in terms of noise level and point distribution. The outcomes demonstrate the feasibility of the mobile robotic platform as a promising technology for automatic and accurate 3D mapping. Full article

This study aims to investigate the effects of the degree of freedom (DOF) and weight of the hand exoskeleton (HE) on hand joint mobility function (ease of movement, movement range) in fine hand use activities. A three-digit passive HE prototype was built to fit each of the 12 participants. Two DOF setups (three DOF, two DOF), two digits’ weight levels (70 g, 140 g), and barehand conditions were tested. A productivity task (performed with Standardized-Nine Hole Peg Test) and motion tasks, both performing the tip pinch and tripod pinch, were conducted to measure the task completion time and the range of motion (ROM) of the digit joints, respectively, using a motion capture system. The perceived ease rating was also measured. The results showed that DOF reduction and weight addition caused a significant task completion time increase and rating drop (p < 0.05). Meanwhile, the DOF reduction increased the ROM reduction of the proximal interphalangeal joints; however, the weight addition caused a correction of the ROM reduction of several joints (p < 0.05) at the tripod pinch. In conclusion, wearing an HE reduces hand joint mobility, especially in lower DOF. However, a certain weight addition may improve joint mobility in terms of the fingers’ movement range. Full article

Particle swarm optimisation (PSO) is a swarm intelligence algorithm used for controlling robotic swarms in applications such as source localisation. However, conventional PSO algorithms consider only the intensity of the received signal. Wavefield signals, such as propagating underwater acoustic waves, permit the measurement of higher order statistics that can be used to provide additional information about the location of the source and thus improve overall swarm performance. Wavefield correlation techniques that make use of such information are already used in multi-element hydrophone array systems for the localisation of underwater marine sources. Additionally, the simplest model of a multi-element array (a two-element array) is characterised by operational simplicity and low-cost, which matches the ethos of robotic swarms. Thus, in this paper, three novel approaches are introduced that enable PSO to consider the higher order statistics available in wavefield measurements. In simulations, they are shown to outperform the standard intensity-based PSO in terms of robustness to low signal-to-noise ratio (SNR) and convergence speed. The best performing approach, cross-correlation bearing PSO (XB-PSO), is capable of converging to the source from as low as −5 dB initial SNR. The original PSO algorithm only manages to converge at 10 dB and at this SNR, XB-PSO converges 4 times faster. Full article

This study proposes a performance index for the dimensional optimization of parallel manipulators with specific tasks. In particular, the index evaluates the dexterity of the mechanism to be designed and compares it with that of the required specific task, e.g., rehabilitation tasks. The proposed index is implemented to design a 3UPS + RPU parallel manipulator for performing physical rehabilitation treatments on lower limbs. First, the condition numbers of both the mechanism and the lower limb are determined. Subsequently, the indexes are compared such that both systems exhibit similar dexterity. As a case study, the approach is implemented in the dimensional synthesis of the 3UPS + RPU parallel manipulator. The optimization approach enables obtaining a dexterity space of the mechanism that best matches that of the lower limb. The results are graphically presented, showing the matching areas of both workspaces, verifying the effectiveness of the proposed index. Full article

In a factory with different kinds of spatial atmosphere (warehouses, corridors, small or large workshops with varying sizes of obstacles and distribution patterns), the robot’s generated paths for navigation tasks mainly depend on the representation of that environment. Hence, finding the best representation for each particular environment is necessary to forge a compromise between length, safety, and complexity of path planning. This paper aims to scrutinize the impact of environment model representation on the performance of an automated guided vehicle (AGV). To do so, a multi-objective cost function, considering the length of the path, its complexity, and minimum distance to obstacles, is defined for a perfect circular robot. Unlike other similar studies, three types of representation, namely quadrangle, irregular triangle, and varying-size irregular triangle, are then utilized to model the environment while applying an inflation layer to the discretized view. Finally, a navigation scenario is tested for different cell decomposition methods and an inflation layer size. The obtained results indicate that a nearly constant coarse size triangular mesh is a good candidate for a fixed-size robot in a non-changing environment. Moreover, the varying size of the triangular mesh and grid cell representations are better choices for factories with changing plans and multi-robot sizes due to the effect of the inflation layer. Based on the definition of a metric, which is a criterion for quantifying the performance of path planning on a representation type, constant or variable size triangle shapes are the only and best candidate for discretization in about 59% of industrial environments. In other cases, both cell types, the square and the triangle, can together be the best representation. Full article

Straight-line needle insertion is a prevalent tool in surgical interventions in the brain, such as Deep Brain Stimulation and Convection-Enhanced Delivery, that treat a range of conditions from Alzheimer’s disease to brain cancer. Using a steerable needle to execute curved trajectories and correct positional deviation could enable more intervention possibilities, while reducing the risk of complication in these procedures. This paper experimentally identifies model parameters using an expectation-maximization (EM) algorithm for two different steerable needle models. The results compared a physically motivated model to the established bicycle needle model and found the former to be preferred for modeling soft brain tissue needle insertion. The results also supported the experimentally parameterized models’ use in future applications such as needle steering control. Full article

This paper aims to improve the positioning accuracy of serial industrial manipulators using force feedback in manufacturing processes by implementing an elasto-geometrical model-based control. Initially, the real-time position control strategy using a force feedback to elastically correct the Tool Center Point (TCP) pose of serial industrial manipulators is detailed. To continue, an efficient model structure identification and calibration is proposed to shorten the elasto-geometrical modeling process. The Virtual Joint Method (VJM) is chosen to iterate and complete the robot stiffness modeling. This method considers that the elastic deformations are only localized at the joints of the robot. An appropriate and original test-model approach allows a minimum of optimization iterations to find the best compromise between complexity and accuracy of the modeling. The proposed approach is illustrated in detail by the Stäubli TX200 robot modeling. Finally, the reliability and responsiveness of the developed control framework is then evaluated through experimental tests in an Incremental Sheet Forming (ISF) context. An average improvement of 70% in trajectory-tracking accuracy is achieved during these tests. Overall, the high accuracy and responsiveness of the developed system demonstrate a promising potential for deploying industrial manipulators to a cost-effective manufacturing processes in industry $4.0$. Full article

Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of actuation system may be able to reduce the amount of damage caused by an unanticipated collision. As a result, elastic joints are expected to outperform stiff joints in complex situations. In this work, the control of a 2-DOF robot arm with elastic actuators is addressed by proposing a two-loop adaptive controller. For the outer control loop, an adaptive sliding mode controller (ASMC) is adopted to deal with uncertainties and disturbance on the load side of the robot arm. For the inner loops, model reference adaptive controllers (MRAC) are utilised to handle the uncertainties on the motor side of the robot arm. To show the effectiveness of the proposed controller, extensive simulation experiments and a comparison with the conventional sliding mode controller (SMC) are carried out. As a result, the ASMC has a 50.35% lower average RMS error than the SMC controller, and a shorter settling time (5% criterion) (0.44 s compared to 2.11 s). Full article

Bin picking is a challenging problem that involves using a robotic manipulator to remove, one-by-one, a set of objects randomly stacked in a container. In order to provide ground truth data for evaluating heuristic or machine learning perception systems, this paper proposes using simulation to create bin picking environments in which a procedural generation method builds entangled tubes that can have curvatures throughout their length. The output of the simulation is an annotated point cloud, generated by a virtual 3D depth camera, in which the tubes are assigned with unique colors. A general metric based on micro-recall is proposed to compare the accuracy of point cloud annotations with the ground truth. The synthetic data is representative of a high quality 3D scanner, given that the performance of a tube modeling system when given 640 simulated point clouds was similar to the results achieved with real sensor data. Therefore, simulation is a promising technique for the automated evaluation of solutions for bin picking tasks. Full article

COVID-19 patients are strongly affected in terms of limb motion when imbedded during the acute phase of the infection, but also during the course of recovery therapies. Peculiarities are investigated for design requirements for medical devices in limb motion assistance for those patients. Solutions are analyzed from existing medical devices to outline open issues to provide guidelines for the proper adaption or for new designs supporting patients against COVID-19 effects. Examples are reported from authors’ activities with cable driven assisting devices. Full article

The foundation and emphasis of robotic manipulator control is Inverse Kinematics (IK). Due to the complexity of derivation, difficulty of computation, and redundancy, traditional IK solutions pose numerous challenges to the operation of a variety of robotic manipulators. This paper develops a Deep Reinforcement Learning (RL) approach for solving the IK problem of a 7-Degree of Freedom (DOF) robotic manipulator using Product of Exponentials (PoE) as a Forward Kinematics (FK) computation tool and the Deep Q-Network (DQN) as an IK solver. The selected approach is architecturally simpler, making it faster and easier to implement, as well as more stable, because it is less sensitive to hyperparameters than continuous action spaces algorithms. The algorithm is designed to produce joint-space trajectories from a given end-effector trajectory. Different network architectures were explored and the output of the DQN was implemented experimentally on a Sawyer robotic arm. The DQN was able to find different trajectories corresponding to a specified Cartesian path of the end-effector. The network agent was able to learn random Bézier and straight-line end-effector trajectories in a reasonable time frame with good accuracy, demonstrating that even though DQN is mainly used in discrete solution spaces, it could be applied to generate joint space trajectories. Full article