Robotics, Volume 8, Issue 4 (December 2019) – 23 articles

The assembly industry is shifting more towards customizable products, or requiring assembly of small batches. This requires a lot of reprogramming, which is expensive because a specialized engineer is required. It would be an improvement if untrained workers could help a cobot to learn an assembly sequence by giving advice. Learning an assembly sequence is a hard task for a cobot, because the solution space increases drastically when the complexity of the task increases. This work introduces a novel method where human knowledge is used to reduce this solution space, and as a result increases the learning speed. The method proposed is the IRL-PBRS method, which uses Interactive Reinforcement Learning (IRL) to learn from human advice in an interactive way, and uses Potential Based Reward Shaping (PBRS), in a simulated environment, to focus learning on a smaller part of the solution space. The method was compared in simulation to two other feedback strategies. The results show that IRL-PBRS converges more quickly to a valid assembly sequence policy and does this with the fewest human interactions. Finally, a use case is presented where participants were asked to program an assembly task. Here, the results show that IRL-PBRS learns quickly enough to keep up with advice given by a user, and is able to adapt online to a changing knowledge base. Full article

Landing safely is the key to successful exploration of the solar system; the mitigation of the connected effects of collision in mechanical systems relies on the conversion of kinetic energy into heat or potential energy. An effective landing-system design should minimize the acceleration acting on the payload. In this paper, we focus on the application of a special class of nonlinear preloaded mechanisms, which take advantage of a variable radius drum (VRD) to produce a constant reactive force during deceleration. Static and dynamic models of the mechanism are presented. Numerical results show that the system allows for very efficient kinetic energy accumulation during impact, approaching the theoretical limit. Full article

Augmenting the human hand with robotic extra fingers is a cutting-edge research topic and has many potential applications, in particular as a compensatory and rehabilitation tool for patients with upper limb impairments. Devices composed of two extra fingers are preferred with respect to single finger devices when reliable grasps, resistance to external disturbances, and higher payloads are required. Underactuation and compliance are design choices that can reduce the device complexity and weight, maintaining the adaptability to different grasped objects. When only one motor is adopted to actuate multiple fingers, a differential mechanism is necessary to decouple finger movements and distribute forces. In this paper, the main features of a wearable device composed of two robotic extra fingers are described and analyzed in terms of kinematics, statics, and mechanical resistance. Each finger is composed of modular phalanges and is actuated with a single tendon. Interphalangeal joints include a passive elastic element that allows restoring the initial reference configuration when the tendon is released. The stiffness of each passive element can be customized in the manufacturing process and can be chosen according to a desired closure movement of the fingers. Another key aspect of the device is the differential system connecting the actuator to the fingers. Full article

Moving from a given position to another with an industrial robot can be a challenging problem when the task is redundant around the tool axis. In this case, there are infinite ways of choosing both the starting and the ending configurations, so that the movement between the given points is not uniquely defined. In this paper, an algorithm that calculates the suboptimal movement between two positions is proposed, which automatically generates a cloud of safe via points around the workpiece and then by exploiting such points finds the suboptimal safe path between the two positions that minimizes movement time. The proposed method, in which the search of the suboptimal path is based on graph theory and the Dijkstra algorithm, can iteratively evaluate a high number of starting and ending configurations in low computational time, allowing performing a reasonably wide search of the suboptimal path within the infinite possible motions between the given points. Full article

This paper provides an overview of collaborative robotics towards manufacturing applications. Over the last decade, the market has seen the introduction of a new category of robots—collaborative robots (or “cobots”)—designed to physically interact with humans in a shared environment, without the typical barriers or protective cages used in traditional robotics systems. Their potential is undisputed, especially regarding their flexible ability to make simple, quick, and cheap layout changes; however, it is necessary to have adequate knowledge of their correct uses and characteristics to obtain the advantages of this form of robotics, which can be a barrier for industry uptake. The paper starts with an introduction of human–robot collaboration, presenting the related standards and modes of operation. An extensive literature review of works published in this area is undertaken, with particular attention to the main industrial cases of application. The paper concludes with an analysis of the future trends in human–robot collaboration as determined by the authors. Full article

In this paper, we investigate the accuracy and the computational efficiency of an IMU-based approach for solving the direct kinematics problem of parallel mechanisms with length-variable linear actuators under dynamic conditions. By avoiding to measure the linear actuators’ lengths and by using orientations instead, a comprehensive, low-cost sensor structure can be obtained that provides a unique solution for the direct kinematics problem. As a representative example, we apply our approach to the planar 3-RPR parallel mechanism, where P denotes active prismatic joints and R denotes passive revolute joints, and investigate the achievable accuracy and robustness on a specially designed experimental device. In this context, we also investigate the effect of sensor fusion on the achievable accuracy and compare our results with those obtained from linear actuators’ lengths when the Newton-Raphson algorithm is used to compute the manipulator platform’s pose iteratively. Finally, we discuss the applicability of inertial measurement units (IMUs) for solving the direct kinematics problem of parallel mechanisms. Full article

With the increasing demand for robots to react and adapt to unforeseen events, it is essential that a robot preserves agility at all times. While manipulability is a common measure to quantify agility at a given joint configuration, an efficient direct evaluation in task space is usually not possible with conventional methods, especially for redundant robots with an infinite number of Inverse Kinematic solutions. Yet, this is essential for global online optimization of a robot posture. In this work, we derive analytical expressions for a conventional 7-degrees of freedom (7-DOF) serial robot structure, which enable the direct evaluation of manipulability from a reduced task space parametrization. The resulting expressions allow array operation and thus achieve very high computational efficiency with vector-optimized programming languages. This direct and simultaneous calculation of the task space manipulability for large numbers of poses benefits many optimization problems in robotic applications. We show applications in global optimization of robot mounting poses, as well as redundancy resolution with global online optimization w.r.t. manipulability. Full article

Many methods have been proposed for avoiding obstacles in robotic systems. However, a robotic system that moves without colliding with obstacles and people, while still being mentally safe to the persons nearby, has not yet been realized. In this paper, we describe the development of a method for a mobile robot to avoid a pedestrian approaching from the front and to pass him/her by while preserving the “public distance” of personal space. We assume a robot that moves along a prerecorded path. When the robot detects a pedestrian using a laser range finder (LRF), it calculates the trajectory to avoid the pedestrian considering their personal space, passes by the pedestrian, and returns to the original trajectory. We introduce a virtual target to control the robot moving along the path, such that it can use the same control strategy as for human-following behavior. We carry out experiments to evaluate the method along three routes, in which the robot functioned without problems. The distance between the robot and the pedestrian was 9.3 m, on average, when the robot started to use avoiding behavior, which is large enough to keep a public distance from a pedestrian. When the robot passed by the pedestrian, the minimum distance between them was 1.19 m, which was large enough for passing safely. Full article

A deep analysis of ankle mechanical properties is a fundamental step in the design of an exoskeleton, especially if it is to be suitable for both adults and children. This study aims at assessing age-related differences of ankle properties using pediAnklebot. To achieve this aim, we enrolled 16 young adults and 10 children in an experimental protocol that consisted of the evaluation of ankle mechanical impedance and kinematic performance. Ankle impedance was measured by imposing stochastic torque perturbations in dorsi-plantarflexion and inversion-eversion directions. Kinematic performance was assessed by asking participants to perform a goal-directed task. Magnitude and anisotropy of impedance were computed using a multiple-input multiple-output system. Kinematic performance was quantified by computing indices of accuracy, smoothness, and timing. Adults showed greater magnitude of ankle impedance in both directions and for all frequencies, while the anisotropy was higher in children. By analyzing kinematics, children performed movements with lower accuracy and higher smoothness, while no differences were found for the duration of the movement. In addition, adults showed a greater ability to stop the movement when hitting the target. These findings can be useful to a proper development of robotic devices, as well as for implementation of specific training programs. Full article

Maintaining engagement is challenging in human–human interaction. When disengagements happen, people try to adapt their behavior with an expectation that engagement will be regained. In human–robot interaction, although socially interactive robots are engaging, people can easily drop engagement while interacting with robots. This paper proposes a multi-layer re-engagement system that applies different strategies through human-like verbal and non-verbal behaviors to regain user engagement, taking into account the user’s attention level and affective states. We conducted a usability test in a robot storytelling scenario to demonstrate technical operation of the system as well as to investigate how people react when interacting with a robot with re-engagement ability. Our usability test results reveal that the system has the potential to maintain a user’s engagement. Our selected users gave positive comments, through open-ended questions, to the robot with this ability. They also rated the robot with the re-engagement ability higher on several dimensions, i.e., animacy, likability, and perceived intelligence. Full article

Smart textiles are flexible materials with interactive capabilities such as sensing, actuation, and computing, and in recent years have garnered considerable interest. Shape-memory alloy (SMA) wire is well-suited for smart textiles due to its high strength, small size, and low mass. However, the contraction of SMA wire is low, limiting its usefulness. One solution to increasing net contraction is to use a long SMA wire and guide it inside a tube that is wound back and forth or coiled inside a smart textile. In this article, we characterize the performance of tube-guided SMA wire actuators. We investigate the effect of turn radius and number of loops, showing that the stroke of an SMA-based system can be improved by up to 69.81% using the tube-guided SMA wire actuator concept. Finally, we investigate how tube-guided SMA wire actuators can be lubricated to improve their performance. Coarse graphite powder and tungsten disulfide lubricant both delivered improvements in stroke compared with an unlubricated system. Full article

Successful manipulation of unknown objects requires an understanding of their physical properties. Infrared thermography has the potential to provide real-time, contactless material characterization for unknown objects. In this paper, we propose an approach that utilizes active thermography and custom multi-channel neural networks to perform classification between samples and regression towards the density property. With the help of an off-the-shelf technology to estimate the volume of the object, the proposed approach is capable of estimating the weight of the unknown object. We show the efficacy of the infrared thermography approach to a set of ten commonly used materials to achieve a 99.1% $R^2$ -fit for predicted versus actual density values. The system can be used with tele-operated or autonomous robots to optimize grasping techniques for unknown objects without touching them. Full article

This paper deals with the control of the sit-to-stand transfer of a biped robotic device (either an autonomous biped robot or a haptic assistive exoskeleton for postural rehabilitation). The control has been synthesized, instead of considering the physiology, analyzing the basic laws of dynamics. The transfer of a human from sitting on a chair to an erect posture is an interesting case study, because it treats biped balance in a two-phase dynamic setting, with an external force disturbance (the chair–pelvis contact) affecting the center of pressure under the feet. At the beginning, a body is sitting, with a fixed pelvis moving with the hips going toward the supporting feet and, contemporaneously, releasing the load from the chair with ankles and knee torques. Then, after lift-off, it reaches and maintains an erect posture. The paper objectives are threefold: identifying the major dynamical determinants of the exercise; sythesizing an automatic control for an autonomous device; proposing an innovative approach for the rehabilitation process with an exoskeleton. For this last objective, the paper extends the idea of the authors of a haptic exoskeleton for rehabilitation. It is driven to control the joints by electromiographical signals from the patient. The two spaces, cartesian (world) and joint, where, respectively, the automatic control and the patient operate, are considered and a technique to blend the two actions is proposed. The exoskeleton is programed to perform the exercise autonomously. Then, during the evolution of the phases of rehabilitation, we postulated to seamlessly move the control from one space (purely autonomous) to another (completely driven by the patient), choosing and keeping the postural tasks and joints (heaps, knees, or ankles) on which to apply each one of the two actions without interaction. Full article

Robot table tennis systems require a vision system that can track the ball position with low latency and high sampling rate. Altering the ball to simplify the tracking using, for instance, infrared coating changes the physics of the ball trajectory. As a result, table tennis systems use custom tracking systems to track the ball based on heuristic algorithms respecting the real-time constrains applied to RGB images captured with a set of cameras. However, these heuristic algorithms often report erroneous ball positions, and the table tennis policies typically need to incorporate additional heuristics to detect and possibly correct outliers. In this paper, we propose a vision system for object detection and tracking that focuses on reliability while providing real-time performance. Our assumption is that by using multiple cameras, we can find and discard the errors obtained in the object detection phase by checking for consistency with the positions reported by other cameras. We provide an open source implementation of the proposed tracking system to simplify future research in robot table tennis or related tracking applications with strong real-time requirements. We evaluate the proposed system thoroughly in simulation and in the real system, outperforming previous work. Furthermore, we show that the accuracy and robustness of the proposed system increases as more cameras are added. Finally, we evaluate the table tennis playing performance of an existing method in the real robot using the proposed vision system. We measure a slight increase in performance compared to a previous vision system even after removing all the heuristics previously present to filter out erroneous ball observations. Full article

The zero moment point ( $ZMP$ ) and the linearized inverted pendulum model linking the $ZMP$ to the center of gravity ( $COG$ ) have an important role in the control of the postural equilibrium (balance) of biped robots and lower-limb exoskeletons. A solution for balance real time control, closing the loop from the joint actual values of the $COG$ and $ZMP$ , has been proposed by Choi. However, this approach cannot be practically implemented: While the $ZMP$ actual value is available from the center of pressure ( $CoP$ ) measured under the feet soles, the $COG$ is not measurable, but it can only be indirectly assessed from the joint-angle measures, the knowledge of the kinematics, and the usually poorly known weight distribution of the links of the chain. Finally, the possible presence of unknown external disturbance forces and the nonlinear, complex nature of the kinematics perturb the simple relationship between the $ZMP$ and $COG$ in the linearized model. The aim of this paper is to offer, starting from Choi’s model, a practical implementation of closed-loop balance control fusing $CoP$ and joint-angle measures, eliminating possible inconsistencies. In order to achieve this result, we introduce a model of the linearized inverted pendulum for an extended estimation, not only of $COG$ and $ZMP$ , but also of external disturbances. This model is then used, instead of Choi’s equations, for estimation and balance control, using ${\mathcal{H}}_{\infty }$ theory. As the $COG$ information is recovered from the joint-angle measures, the identification of a statistically equivalent serial chain ( $SESC$ ) linking the $COG$ to the joint angles is also discussed. Full article

Understanding user perceptions is particularly important in developing social robots, which tend to have a high degree of interaction with humans. However, psychometric measures of robot acceptability have only recently started to become available. The present critical review outlines the psychometrically validated questionnaires to measure social acceptability factors related to social robots. Using an iterative search strategy, articles were identified that reported on the development of such questionnaires as well as information about their psychometric properties. Six questionnaires were identified that provide researchers with options varying in length, content, and factor structure. Two of these questionnaires inquire about attitudes and anxieties related to robots, while two others capture a larger range of attitudes that extends to positive and neutral aspects as well. One of the questionnaires reviewed here was specific to inquiring about ethical issues related to the use of social robots for therapy with children with autism, and the last one was designed to provide an assessment of expectations of participants prior to interacting with a robot. Overall, the use of robot acceptability measures is still relatively new, and further psychometric work is necessary to provide confidence in the validity and reliability of these scales. Full article

One major challenge for microrobots is to penetrate and effectively move through viscoelastic biological tissues. Most existing microrobots can only propel in viscous liquids. Recent advances demonstrate that sub-micron robots can actively penetrate nanoporous biological tissue, such as the vitreous of the eye. However, it is still difficult to propel a micron-sized device through dense biological tissue. Here, we report that a special twisted helical shape together with a high aspect ratio in cross-section permit a microrobot with a diameter of hundreds-of-micrometers to move through mouse liver tissue. The helical microrobot is driven by a rotating magnetic field and localized by ultrasound imaging inside the tissue. The twisted ribbon is made of molybdenum and a sharp tip is chemically etched to generate a higher pressure at the edge of the propeller to break the biopolymeric network of the dense tissue. Full article

The manipulation of unknown objects is a problem of special interest in robotics since it is not always possible to have exact models of the objects with which the robot interacts. This paper presents a simple strategy to manipulate unknown objects using a robotic hand equipped with tactile sensors. The hand configurations that allow the rotation of an unknown object are computed using only tactile and kinematic information, obtained during the manipulation process and reasoning about the desired and real positions of the fingertips during the manipulation. This is done taking into account that the desired positions of the fingertips are not physically reachable since they are located in the interior of the manipulated object and therefore they are virtual positions with associated virtual contact points. The proposed approach was satisfactorily validated using three fingers of an anthropomorphic robotic hand (Allegro Hand), with the original fingertips replaced by tactile sensors (WTS-FT). In the experimental validation, several everyday objects with different shapes were successfully manipulated, rotating them without the need of knowing their shape or any other physical property. Full article

One of the challenges in robotic grasping tasks is the problem of detecting whether a grip is stable or not. The lack of stability during a manipulation operation usually causes the slippage of the grasped object due to poor contact forces. Frequently, an unstable grip can be caused by an inadequate pose of the robotic hand or by insufficient contact pressure, or both. The use of tactile data is essential to check such conditions and, therefore, predict the stability of a grasp. In this work, we present and compare different methodologies based on deep learning in order to represent and process tactile data for both stability and slip prediction. Full article

Background: The application of continuum manipulators as assistive robots is discussed and tested through the use of Bendy ARM, a simple manually teleoperated tendon driven continuum manipulator prototype. Methods: Two rounds of user testing were performed to evaluate the potential of this arm to aid people living with disabilities in completing activities of daily living. Results: In the first round of user testing, 14 able-bodied subjects successfully completed the prescribed task (pick-and-place) using multiple control schemes after being given a brief introduction and one minute of practice with each scheme. In the second round of user testing, subjects ( $n=3$ ) demonstrated between 29.5 and 48.9 percent improvement in completion time across twelve trials of a peg-in-hole task, and between 8.4 and 33.8 percent improvement across six trials of a task involving opening and closing a drawer. Conclusion: Based on these results, it is posited that continuum manipulators merit further consideration as a safer and more cost-effective alternative to existing commercially available assistive robotic manipulators. Full article

Field robotics is a very important sub-field of robotic systems, focusing on systems which need to navigate in open, unpredictable terrain and perform non-repetitive missions while monitoring and reacting to their surroundings. General testing and validation standards for larger robotic systems, including field robots, have not been developed yet due to a variety of factors including disagreement over terminology and functional/performance requirements. This tutorial presents a generalized, step-by-step system-level test plan for field robots under manual, semi-autonomous/tele-operated, and autonomous control schemes; this includes a discussion of the requirements and testing parameters, and a set of suggested safety, communications, and behavior evaluation test courses. The testing plan presented here is relevant to both commercial and academic research into field robotics, providing a standardized general testing procedure. Full article

The optimal tracking problem is addressed in the robotics literature by using a variety of robust and adaptive control approaches. However, these schemes are associated with implementation limitations such as applicability in uncertain dynamical environments with complete or partial model-based control structures, complexity and integrity in discrete-time environments, and scalability in complex coupled dynamical systems. An online adaptive learning mechanism is developed to tackle the above limitations and provide a generalized solution platform for a class of tracking control problems. This scheme minimizes the tracking errors and optimizes the overall dynamical behavior using simultaneous linear feedback control strategies. Reinforcement learning approaches based on value iteration processes are adopted to solve the underlying Bellman optimality equations. The resulting control strategies are updated in real time in an interactive manner without requiring any information about the dynamics of the underlying systems. Means of adaptive critics are employed to approximate the optimal solving value functions and the associated control strategies in real time. The proposed adaptive tracking mechanism is illustrated in simulation to control a flexible wing aircraft under uncertain aerodynamic learning environment. Full article