Robotics

Condition monitoring of industrial robots has the potential to decrease downtimes in highly automated production systems. In this context, we propose a new method to evaluate health indicators for this application and suggest a new health indicator (HI) based on vibration data measurements, Short-time Fourier transform and Z-scores. By executing the method, we find that the proposed health indicator can detect varying faults better, has lower temperature sensitivity and works better in instationary velocity regimes compared to several state-of-the-art HIs. A discussion of the validity of the results concludes our contribution. Full article

The operation and maintenance of converter stations (also known as valve halls) in high voltage DC (HVDC) grids is a key element in long-term, reliable and stable operation, especially in inherently adverse offshore environments. However, the nature of the electromagnetic field environment inside HVDC valve halls presents a challenge for the operation of traditional off-shelf inspection robots. In this paper, the impact of the external magnetic field on the operation of an inspection UAV’s propulsion motors is assessed. An experimental method is proposed to simulate the maximum magnetic field interference to off-shelf UAV motors, which can be used to identify their suitability for use in HVDC valve halls inspection robots. The paper’s experimental results compare the performance of direct torque control and field-oriented control algorithms for propulsion motors under the influence of external magnetic flux. Under the influence of a 177 mT external magnetic field, it was found that using direct torque control, the motor rotational velocity steady-state error was up to 55%. With field-oriented control, the steady-state error was 0%, however the peak-to-peak current draw increased by up to 567%. Full article

This paper describes a novel autonomous ground vehicle that is designed for exploring unknown environments which contain sources of ionising radiation, such as might be found in a nuclear disaster site or a legacy nuclear facility. While exploring the environment, it is important that the robot avoids radiation hot spots to minimise breakdowns. Broken down robots present a real problem: they not only cause the mission to fail but they can block access routes for future missions. Until now, such robots have had no autonomous gamma radiation avoidance capabilities. New software algorithms are presented that allow radiation measurements to be converted into a format in which they can be integrated into the robot’s navigation system so that it can actively avoid receiving a high radiation dose during a mission. An unmanned ground vehicle was fitted with a gamma radiation detector and an autonomous navigation package that included the new radiation avoidance software. The full system was evaluated experimentally in a complex semi-structured environment that contained two radiation sources. In the experiment, the robot successfully identified both sources and avoided areas that were found to have high levels of radiation while navigating between user defined waypoints. This advancement in the state-of-the-art has the potential to deliver real benefit to the nuclear industry, in terms of both increased chance of mission success and reduction of the reliance on human operatives to perform tasks in dangerous radiation environments. Full article

This article describes an algorithm for the online extrapolation of hand-motion during remote welding. The aim is to overcome the spatial limitations of the human welder’s arms in order to cover a larger workspace with a continuous weld seam and to substantially relieve the welder from strain and fatigue. Depending on the sampled hand-motion data, an extrapolation of the given motion patterns is achieved by decomposing the input signals in a linear direction and a periodic motion component. An approach to efficiently determine the periodicity using a sampled autocorrelation function and the subsequent application of parameter identification using a spline function are presented in this paper. The proposed approach is able to resemble all practically relevant motion patterns and has been validated successfully on a remote welding system with limited input space and audio-visual feedback by an experienced welder. Full article

In this paper, a nonlinear robust Fast Terminal Sliding Mode Controller (FTSMC) is designed to control and stabilize a new reconfigurable Unmanned Aerial Vehicle (UAV) in the presence of uncertain and variable parameters. The studied UAV is an over-actuated system due the number of actuator control inputs. It can modify the length and the angles between its four arms in different ways, which result an important variation in its Center of Gravity (CoG), inertia, and control matrix. The proposed FTSMC offers many advantages such as, reaching the desired states in a finite-time unlike the conventional sliding mode, robustness vis-a-vis uncertain and unknown parameters, fast convergence towards the sliding surface, high accuracy and reducing the chattering phenomena. Furthermore, the closed-loop stability of the this UAV is ensured by the Lyapunov theory. The eight actuators used to rotate and extend the UAV arms are controlled by simple Proportional Integral Derivative (PID) controllers. Lastly, the robustness and efficiency of the proposed controller are evaluated through a flight scenario, where the UAV geometric parameters are variable over time. Full article

In this work, we consider the motion control problem for a platoon of unicycle robots operating within an obstacle-cluttered workspace. Each robot is equipped with a proximity sensor that allows it to perceive nearby obstacles as well as a camera to obtain its relative position with respect to its preceding robot. Additionally, no robot other than the leader of the team is able to localize itself within the workspace and no centralized communication network exists, i.e., explicit information exchange between the agents is unavailable. To tackle this problem, we adopt a leader–follower architecture and propose a novel, decentralized control law for each robot-follower, based on the Prescribed Performance Control method, which guarantees collision-free tracking and visual connectivity maintenance by ensuring that each follower maintains its predecessor within its camera field of view while keeping static obstacles out of the line of sight for all time. Finally, we verify the efficacy of the proposed control scheme through extensive simulations. Full article

This paper outlines the design of a novel mechatronic system for semi-automatic inspection and white-water in-pipe obstruction removals without the need for destructive methods or specialized manpower. The device is characterized by a lightweight structure and high transportability. It is composed by a front, a rear and a central module that realize the worm-like locomotion of the robot with a specifically designed driving mechanism for the straight motion of the robot along the pipeline. The proposed mechatronic system is easily adaptable to pipes of various sizes. Each module is equipped with a motor that actuates three slider-crank-based mechanisms. The central module incorporates a length-varying mechanism that allows forward and backward locomotion. The device is equipped with specific low-cost sensors that allow an operator to monitor the device and locate an obstruction in real time. The movement of the device can be automatic or controlled manually by using a specific user-friendly control board and a laptop. Preliminary laboratory tests are reported to demonstrate the engineering feasibility and effectiveness of the proposed design, which is currently under patenting. Full article

This paper set out to investigate the usefulness of solving collision avoidance problems with the help of deep reinforcement learning in an unknown environment, especially in compact spaces, such as a narrow corridor. This research aims to determine whether a deep reinforcement learning-based collision avoidance method is superior to the traditional methods, such as potential field-based methods and dynamic window approach. Besides, the proposed obstacle avoidance method was developed as one of the capabilities to enable each robot in a novel robotic system, namely the Self-reconfigurable and Transformable Omni-Directional Robotic Modules (STORM), to navigate intelligently and safely in an unknown environment. A well-conceived hardware and software architecture with features that enable further expansion and parallel development designed for the ongoing STORM projects is also presented in this work. A virtual STORM module with skid-steer kinematics was simulated in Gazebo to reduce the gap between the simulations and the real-world implementations. Moreover, comparisons among multiple training runs of the neural networks with different parameters related to balance the exploitation and exploration during the training process, as well as tests and experiments conducted in both simulation and real-world, are presented in detail. Directions for future research are also provided in the paper. Full article

A multi-AGV based logistic system is typically associated with two fundamental problems, critical for its overall performance: the AGV’s route planning for collision and deadlock avoidance; and the task scheduling to determine which vehicle should transport which load. Several heuristic functions can be used according to the application. This paper proposes a time-based algorithm to dynamically control a fleet of Autonomous Guided Vehicles (AGVs) in an automatic warehouse scenario. Our approach includes a routing algorithm based on the A* heuristic search (TEA*—Time Enhanced A*) to generate free-collisions paths and a scheduling module to improve the results of the routing algorithm. These modules work cooperatively to provide an efficient task execution time considering as basis the routing algorithm information. Simulation experiments are presented using a typical industrial layout for 10 and 20 AGVs. Moreover, a comparison with an alternative approach from the state-of-the-art is also presented. Full article

There is considerable interest in multirobot systems capable of performing spatially distributed, hazardous, and complex tasks as a team leveraging the unique abilities of humans and automated machines working alongside each other. The limitations of human perception and cognition affect operators’ ability to integrate information from multiple mobile robots, switch between their spatial frames of reference, and divide attention among many sensory inputs and command outputs. Automation is necessary to help the operator manage increasing demands as the number of robots (and humans) scales up. However, more automation does not necessarily equate to better performance. A generalized robot confidence model was developed, which transforms key operator attention indicators to a robot confidence value for each robot to enable the robots’ adaptive behaviors. This model was implemented in a multirobot test platform with the operator commanding robot trajectories using a computer mouse and an eye tracker providing gaze data used to estimate dynamic operator attention. The human-attention-based robot confidence model dynamically adapted the behavior of individual robots in response to operator attention. The model was successfully evaluated to reveal evidence linking average robot confidence to multirobot search task performance and efficiency. The contributions of this work provide essential steps toward effective human operation of multiple unmanned vehicles to perform spatially distributed and hazardous tasks in complex environments for space exploration, defense, homeland security, search and rescue, and other real-world applications. Full article

A closed-form dynamic model of the planar multi-link flexible manipulator is presented. The assumed modes method is used with the Lagrangian formulation to obtain the dynamic equations of motion. Explicit equations of motion are derived for a three-link case assuming two modes of vibration for each link. The eigenvalue problem associated with the mass boundary conditions, which changes with the robot configuration and payload, is discussed. The time-domain simulation results and frequency-domain analysis of the dynamic model are presented to show the validity of the theoretical derivation. Full article

In this paper, the effect of strain rate on the output signal of highly stretchable interdigitated capacitive (IDC) strain sensors is studied. IDC sensors fabricated with pristine Ecoflex and a composite based on 40 wt% of 200 nm barium titanate (BTO) dispersed in a silicone elastomer (Ecoflex 00-30^TM) were subjected to 1000 stretch and relax cycles to study the effect of dynamic loading conditions on the output signal of the IDC sensor. It was observed that the strain rate has no effect on the output signal of IDC sensor. To study the non-linear elastic behaviour of pristine Ecoflex and composites based on 10, 20, 30, 40 wt% of 200 nm BTO filler dispersed in a silicone elastomer, we conducted uniaxial tensile testing to failure at strain rates of ~5, ~50, and ~500 mm/min. An Ogden second-order model was used to fit the uniaxial tensile test data to understand the non-linearity in the stress-strain responses of BTO-Ecoflex composite at different strain rates. The decrease in Ogden parameters (α₁ and α₂) indicates the decrease in non-linearity of the stress-strain response of the composite with an increase in filler loading. Scanning electronic microscopy analysis was performed on the cryo-fractured pristine Ecoflex and 10, 20, 30, and 40 wt% of BTO-Ecoflex composites, where it was found that 200 nm BTO is more uniformly distributed in Ecoflex at a higher filler loading levels (40 wt% 200 nm BTO). Therefore, an IDC sensor was fabricated based on a 40 wt% 200 nm BTO-Ecoflex composite and mounted on an elastic elbow sleeve with supporting electronics, and successfully functioned as a reliable and robust flexible sensor, demonstrating an application to measure the bending angle of an elbow at slow and fast movement of the arm. A linear relationship with respect to the elbow bending angle was observed between the IDC sensor output signal under a 50% strain and the deflection of the elbow of hand indicating its potential as a stretchable, flexible, and wearable sensor. Full article

In gaze-based Human-Robot Interaction (HRI), it is important to determine human visual intention for interacting with robots. One typical HRI interaction scenario is that a human selects an object by gaze and a robotic manipulator will pick up the object. In this work, we propose an approach, GazeEMD, that can be used to detect whether a human is looking at an object for HRI application. We use Earth Mover’s Distance (EMD) to measure the similarity between the hypothetical gazes at objects and the actual gazes. Then, the similarity score is used to determine if the human visual intention is on the object. We compare our approach with a fixation-based method and HitScan with a run length in the scenario of selecting daily objects by gaze. Our experimental results indicate that the GazeEMD approach has higher accuracy and is more robust to noises than the other approaches. Hence, the users can lessen cognitive load by using our approach in the real-world HRI scenario. Full article

The advent of sophisticated robotics and AI technology makes sending humans into hazardous and distant environments to carry out inspections increasingly avoidable. Being able to send a robot, rather than a human, into a nuclear facility or deep space is very appealing. However, building these robotic systems is just the start and we still need to carry out a range of verification and validation tasks to ensure that the systems to be deployed are as safe and reliable as possible. Based on our experience across three research and innovation hubs within the UK’s “Robots for a Safer World” programme, we present an overview of the relevant techniques and challenges in this area. As the hubs are active across nuclear, offshore, and space environments, this gives a breadth of issues common to many inspection robots. Full article

Robots that incorporate social norms in their behaviors are seen as more supportive, friendly, and understanding. Since it is impossible to manually specify the most appropriate behavior for all possible situations, robots need to be able to learn it through trial and error, by observing interactions between humans, or by utilizing theoretical knowledge available in natural language. In contrast to the former two approaches, the latter has not received much attention because understanding natural language is non-trivial and requires proper grounding mechanisms to link words to corresponding perceptual information. Previous grounding studies have mostly focused on grounding of concepts relevant to object manipulation, while grounding of more abstract concepts relevant to the learning of social norms has so far not been investigated. Therefore, this paper presents an unsupervised cross-situational learning based online grounding framework to ground emotion types, emotion intensities and genders. The proposed framework is evaluated through a simulated human–agent interaction scenario and compared to an existing unsupervised Bayesian grounding framework. The obtained results show that the proposed framework is able to ground words, including synonyms, through their corresponding perceptual features in an unsupervised and open-ended manner, while outperfoming the baseline in terms of grounding accuracy, transparency, and deployability. Full article

Human–robot collaboration is currently one of the frontiers of industrial robot implementation. In parallel, the use of robots and robotic devices is increasing in several fields, substituting humans in “4D”—dull, dirty, dangerous, and delicate—tasks, and such a trend is boosted by the recent need for social distancing. New challenges in safety assessment and verification arise, due to both the closer and closer human–robot interaction, common for the different application domains, and the broadening of user audience, which is now very diverse. The present paper discusses a cross-domain approach towards the definition of step-by-step validation procedures for collaborative robotic applications. To outline the context, the standardization framework is analyzed, especially from the perspective of safety testing and assessment. Afterwards, some testing procedures based on safety skills, developed within the framework of the European project COVR, are discussed and exemplary presented. Full article

Worldwide, millions of kilometres of sewers are constructed from concrete pipes. Unfortunately, concrete sewers are susceptible to corrosion from biogenic hydrogen sulphide, and, though they may pass visual inspection, their ability to hold together under load may be degraded. This paper presents the design of a teleoperated robot with a protractible probe, that allows an operator to apply a localised load to selected points within a concrete sewer pipe. We report findings from laboratory and field trials of our prototype, with initial results suggesting that this approach has the potential to contribute useful information to sewer maintenance planning. Full article

This study was conducted to develop robot prototypes of three models that navigate mallards to achieve high-efficiency rice-duck farming. We examined two robotics navigation approaches based on imprinting and feeding. As the first approach, we used imprinting applied to baby mallards. They exhibited follow behavior to our first prototype after imprinting. Experimentally obtained observation results revealed the importance of providing imprinting immediately up to one week after hatching. As another approach, we used feed placed on the top of our second prototype. Experimentally obtained results showed that adult mallards exhibited wariness not only against the robot, but also against the feeder. After relieving wariness with provision of more than one week time to become accustomed, adult mallards ate feed in the box on the robot. However, they ran away immediately at a slight movement. Based on this confirmation, we developed the third prototype as an autonomous mobile robot aimed for mallard navigation in a paddy field. The body width is less than the length between rice stalks. After checking the waterproof capability of a body waterproof box, we conducted an indoor driving test for manual operation. Moreover, we conducted outdoor evaluation tests to assess running on an actual paddy field. We developed indoor and outdoor image datasets using an onboard monocular camera. For the outdoor image datasets, our segmentation method based on SegNet achieved semantic segmentation for three semantic categories. For the indoor image datasets, our prediction method based on CNN and LSTM achieved visual prediction for three motion categories. Full article

We describe the implementation of a bespoke two arm hydraulically actuated robotic platform which is used to semi-autonomously cut approximately 50 mm diameter pipes of three different materials: cardboard, ABS plastic and aluminium. The system is designed to be utilised within radiologically active environments where human access is limited due to dose limits and thus remote operation is greatly beneficial. The remotely located operator selects the object from an image via a bespoke algorithm featuring a COTS 3D vision system, along with the desired positions for gripping with one manipulator, and cutting with the other. A pseudo-Jacobian inverse kinematic technique and a programmable automation controller are used to achieve the appropriate joint positions within the dual arm robotic platform. In this article, we present the latest developments to the system and the lessons learnt from the new cutting experiments with a reciprocating saw. A comparison to tele-operated control and manual cutting is also made, with this technique shown to be slower than manual cutting, but faster than pure tele-operational control, where the requirements for highly trained users and operator fatigue are further deleterious factors. Full article