It is challenging to find optimum kinematic designs for non-standard robotic manipulators, e.g., medical, nuclear, and space manipulators, which are demanded to adapt to arbitrary complex tasks in constraints. Such design optimization can be modelled as a multi-dimensional non-convex optimization problem with nonlinear constrained conditions. However, it is non-trivial to ensure the essential reachability condition, i.e., the existence of continuous trajectories between demand positions for serial articulated manipulators, given complex spatial constraints, like obstacles and boundaries. Traditional solutions integrate standard motion planning or inverse kinematics algorithms within a kinematic-design optimization process, resulting in significant demand for time and computing resources. To accelerate design optimization at improved efficiency, we design a novel robust design framework built on a new kinematic design synthesis, which allows for simultaneously optimizing dimension and topology of a serial manipulator's kinematics for arbitrary tasks in constrained environments, using a generalised parametric kinematic model. Significantly, in contrast to standard solutions, we develop a novel computationally effective reachability verification method, which rapidly aborts infeasible motions by exploiting efficient collision checks, based on the Rapidly-exploring Random Tree (RRT) algorithm. The effectiveness of the proposed design framework is verified and evaluated by comparing to baseline benchmarks. Results demonstrate the novel design framework can accelerate kinematic design optimization by an order of magnitude compared to the current state-of-the-art, and optimise link dimension and joint type simultaneously of serial robots for cluttered environments.

In hazardous environments like nuclear facilities, robotic systems are essential for executing tasks that would otherwise expose humans to dangerous radiation levels, which pose severe health risks and can be fatal. However, many operations in the nuclear environment require teleoperating robots, resulting in a significant cognitive load on operators as well as physical strain over extended periods of time. To address this challenge, we propose enhancing the teleoperation system with an assistive model capable of predicting operator intentions and dynamically adapting to their needs. The machine learning model processes robotic arm force data, analyzing spatiotemporal patterns to accurately detect the ongoing task before its completion. To support this approach, we collected a diverse dataset from teleoperation experiments involving glovebox tasks in nuclear applications. This dataset encompasses heterogeneous spatiotemporal data captured from the teleoperation system. We employ a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model to learn and forecast operator intentions based on the spatiotemporal data. By accurately predicting these intentions, the robot can execute tasks more efficiently and effectively, requiring minimal input from the operator. Our experiments validated the model using the dataset, focusing on tasks such as radiation surveys and object grasping. The proposed approach demonstrated an F1-score of 89% for task classification and an F1-score of 86% classification forecasted operator intentions over a 5-second window. These results highlight the potential of our method to improve the safety, precision, and efficiency of robotic operations in hazardous environments, thereby significantly reducing human radiation exposure.

Tele-manipulation is indispensable for the nuclear industry since teleoperated robots cancel the radiation hazard problem for the operator. The majority of the teleoperated solutions used in the nuclear industry rely on bilateral teleoperation, utilizing a variation of the 4-channel architecture, where the motion and force signals of the local and remote robots are exchanged in the communication channel. However, the performance limitation of teleoperated robots for nuclear decommissioning tasks is not clearly answered in the literature. In this study, we assess the task performance in bilateral tele-manipulation for radiation surveying in gloveboxes and compare it to radiation surveying of a glovebox operator. To analyze the performance, an experimental setup suitable for human operation (manual operation) and tele-manipulation is designed. Our results showed that a current commercial off-the-shelf (COTS) teleoperated robotic manipulation solution is flexible, yet insufficient, as its task performance is significantly lower when compared to manual operation and potentially hazardous for the equipment inside the glovebox. Finally, we propose a set of potential solutions, derived from both our observations and expert interviews, that could improve the performance of teleoperation systems in glovebox environments in future work.

In the last few decades, several approaches have been presented to accomplish tasks with robots or autonomous systems in a glovebox; nevertheless, in nuclear facilities, risky operations are still executed by humans that guarantee a high manipulation capability and dexterity. Inside the gloveboxes, robotic devices have to operate in cluttered environments, or environments with limited space for movement; therefore, it is of significant interest to identify grasping poses that are feasible within such constrained environments. In this paper, we present and experimentally evaluate a strategy to synthesise optimal grasps considering geometric primitives for a manipulation systems in a constrained environment. The novel strategy has been experimentally evaluated in a cluttered environment (as a glovebox mock-up) with realistic objects, and the efficacy of the proposed grasping algorithm is proposed.

For gaining proficiency in physical human-robot interactions, it is crucial for engineering students to be provided with the opportunity to gain hands-on experience with robotic devices that feature kinesthetic feedback. In this article, we propose HandsOn-SEA, a low-cost, single degree-of-freedom, force-controlled educational robot with series elastic actuation and introduce educational modules for the use of the device to allow students to experience the fundamental performance trade-offs inherent in robotic systems. The novelty of the proposed robot is due to the deliberate introduction of a compliant element between the actuator and the handle, whose deflections are measured to perform closed-loop force control. As an admittance-type robot, HandsOn-SEA relies on force feedback to achieve the desired level of safety and transparency and complements the existing impedance-type educational robots. We present the integration of HandsOn-SEA into the robotics curriculum, by providing guidelines for its use in a senior level robotics course, to help students experience the challenges involved in the synergistic design and control of robotic devices. We systematically evaluate the efficacy of the device in a robotics course delivered for five semesters and provide evidence that HandsOn-SEA is effective in instilling fundamental concepts and trade-offs in the design and control of robotic devices.

The nuclear industry has some of the most extreme environments in the world, with radiation levels and extremely harsh conditions restraining human access to many facilities. One method for enabling minimal human exposure to hazards under these conditions is through the use of gloveboxes that are sealed volumes with controlled access for performing handling. While gloveboxes allow operators to perform complex handling tasks, they put operators at considerable risk from breaking the confinement and, historically, serious examples including punctured gloves leading to lifetime doses have occurred. To date, robotic systems have had relatively little impact on the industry, even though it is clear that they offer major opportunities for improving productivity and significantly reducing risks to human health. This work presents the challenges of robotic and AI solutions for nuclear gloveboxes, and introduces a step forward for bringing cutting-edge technology to gloveboxes. The problem statement and challenges are highlighted and then an integrated demonstrator is proposed for robotic handling in nuclear gloveboxes for nuclear material handling. The proposed approach spans from tele-manipulation to shared autonomy, computer vision solutions for robotic manipulation to machine learning solutions for condition monitoring.

In today's automation driven manufacturing environments, emerging technologies like cobots (collaborative robots) and augmented reality interfaces can help integrating humans into the production workflow to benefit from their adaptability and cognitive skills. In such settings, humans are expected to work with robots side by side and physically interact with them. However, the trade-off between stability and transparency is a core challenge in the presence of physical human robot interaction (pHRI). While stability is of utmost importance for safety, transparency is required for fully exploiting the precision and ability of robots in handling labor intensive tasks. In this work, we propose a new variable admittance controller based on fractional order control to handle this trade-off more effectively. We compared the performance of fractional order variable admittance controller with a classical admittance controller with fixed parameters as a baseline and an integer order variable admittance controller during a realistic drilling task. Our comparisons indicate that the proposed controller led to a more transparent interaction compared to the other controllers without sacrificing the stability. We also demonstrate a use case for an augmented reality (AR) headset which can augment human sensory capabilities for reaching a certain drilling depth otherwise not possible without changing the role of the robot as the decision maker.

Physical human-robot interaction (pHRI) integrates the benefits of human operator and a collaborative robot in tasks involving physical interaction, with the aim of increasing the task performance. However, the design of interaction controllers that achieve safe and transparent operations is challenging, mainly due to the contradicting nature of these objectives. Knowing that attaining perfect transparency is practically unachievable, controllers that allow better compromise between these objectives are desirable. In this article, we propose a multicriteria optimization framework, which jointly optimizes the stability robustness and transparency of a closed-loop pHRI system for a given interaction controller. In particular, we propose a Pareto optimization framework that allows the designer to make informed decisions by thoroughly studying the tradeoff between stability robustness and transparency. The proposed framework involves a search over the discretized controller parameter space to compute the Pareto front curve and a selection of controller parameters that yield maximum attainable transparency and stability robustness by studying this tradeoff curve. The proposed framework not only leads to the design of an optimal controller, but also enables a fair comparison among different interaction controllers. In order to demonstrate the practical use of the proposed approach, integer and fractional order admittance controllers are studied as a case study and compared both analytically and experimentally. The experimental results validate the proposed design framework and show that the achievable transparency under fractional order admittance controller is higher than that of integer order one, when both controllers are designed to ensure the same level of stability robustness.

This paper reports on a study which investigated whether the addition of haptics (virtual touch) to a three-dimensional (3D) virtual reality (VR) simulation promotes learning of key concepts in biology for students aged 12 to 13 years. We developed a virtual model of a section of the cell membrane and a haptic-enabled interface that allows students to interact with the model and to manipulate objects in the model. Students, in two schools in England, worked collaboratively on activities, in pairs, designed to support learning of key difficult concepts. These concepts included the dynamic nature of the cell membrane, passive diffusion and facilitated diffusion. Findings from observation of the activities and student interviews revealed that students were very positive about using the system and believed that being able to feel structures and movements within the model assisted their learning. Results of pre- and post-tests of conceptual knowledge showed significant knowledge gains but there were no significant differences between the haptic and non-haptic condition.

This paper reports on a study which investigated whether the addition of haptics (virtual touch) to a 3D virtual reality (VR) simulation promotes understanding of key nanoscale concepts in membrane systems for students aged 12 to 13. We developed a virtual model of a section of the cell membrane and a haptic enabled interface that enables students to interact with the model and to manipulate objects in the model. Students, in two schools in England, worked collaboratively in pairs on activities designed to develop their understanding of key concepts of cell membrane function. Results of pre-and post-tests of conceptual knowledge and understanding showed significant knowledge gains but there were no significant differences between the haptic and non-haptic condition. However, findings from observation of the activities and student interviews revealed that students were very positive about using the system and believed that being able to feel structures and manipulate objects within the model assisted their learning. We examine some of the design challenges and issues affecting the perception of haptic feedback.

The use of haptic systems in the classroom for enhancing science education is an underexplored area. In the education literature, it has been reported that certain concepts in science education are difficult for students to grasp and, as a result, misconceptions can be formed in the students’ knowledge. We conducted a study with 62 Year 8 (typically 12–13 years old) students who used a haptic application to study cell biology, specifically the concept of diffusion across a cell membrane. The preliminary analysis of the feedback from the students suggests opportunities for haptic applications to enhance their learning, and also highlights a number of points to consider in the design of the application, including the choice of haptic interface and the design of the virtual environment.

Computational thinking lies at the intellectual core of computing. Promoting computational thinking ability requires that students are provided with a clear understanding of the fundamental principles and concepts of computer science, including abstraction, logic, algorithms, and data representation. We propose to use force-feedback educational robotic devices for hands-on teaching of computational thinking. The addition of haptic feedback for teaching abstract concepts of computer science offers several advantages, as haptic feedback (i) enables an effective means of data hiding, (ii) ensures a high level of student engagement by adding another pathway for perception and enabling active physical interaction, and (iii) improves student motivation through the novelty effect. Moreover, visually impaired students may benefit from replacement of visualization with haptic feedback. We present a force-feedback application for teaching sorting algorithms and report initial student evaluations of integrating haptics to promote computational thinking.

In physical human-robot interaction (pHRI), the cognitive skill of a human is combined with the accuracy, repeatability and strength of a robot.While the promises and potential outcomes of pHRI are glamorous, the control of such coupled systems is challenging in many aspects.In this paper, we propose a new controller, fractional order admittance controller, for pHRI systems.The stability analysis of the new control system with human in-the-loop is performed and the interaction performance is investigated experimentally with 10 subjects during a task imitating a contact with a stiff environment.The results show that the fractional order controller is more robust than the standard admittance controller and helps to reduce the human effort in task execution.

This paper discusses the rationales and design considerations for developing the use of haptics (virtual touch) for learning aspects of cell biology in secondary schools. The paper considers issues in understanding concepts in cell biology and how a 3-D environment enabled by haptics could support learning of difficult concepts. In this endeavour, a number of educational and design challenges need to be addressed. First we need to identify the level of detail and realism that will support learning and visualisation rather than confuse through its overcomplexity or create misconceptions through oversimplification. Secondly we need to integrate the use of the 3-D environment into classroom teaching by identifying relevant curriculum and pedagogical challenges and solutions. Significant design challenges include navigating the content and scale changes involved in moving between the visible, microscopic and nanoscale in an intuitive and realistic way and enabling collaborative learning.

An unexplored application area for haptics is in secondary education. This is a challenging environment because not only does it shift the role of the haptic interface from an aid to learning a skill to become a mechanism to manipulate 3D virtual content, but it adds further technical and educational challenges. In this work, we investigate the efficacy of haptic system in TEL of science classes.

For gaining proficiency in physical human-robot interaction (pHRI), it is crucial for engineering students to be provided with the opportunity to physically interact with and gain hands-on experience on design and control of force-feedback robotic devices. We present a single degree of freedom educational robot that features series elastic actuation and relies on closed loop force control to achieve the desired level of safety and transparency during physical interactions. The proposed device complements the existing impedance-type Haptic Paddle designs by demonstrating the challenges involved in the synergistic design and control of admittance-type devices. We present integration of this device into pHRI education, by providing guidelines for the use of the device to allow students to experience the performance trade-offs inherent in force control systems, due to the non-collocation between the force sensor and the actuator. These exercises enable students to modify the mechanical design in addition to the controllers, by assigning different levels of stiffness values to the compliant element, and characterize the effects of these design choices on the closed-loop force control performance of the device. We also report initial evaluations of the efficacy of the device for pHRI studies.

Fractional order (FO) calculus—a generalization of the traditional calculus to arbitrary order differointegration-is an effective mathematical tool that broadens the modeling boundaries of the familiar integer order calculus. The effectiveness of this remarkable mathematical tool has been observed in many practical applications. For instance, FO models enable faithful representation of viscoelastic materials that exhibit frequency dependent stiffness and damping characteristics within a single mechanical element. In this dissertation, we propose and analyze the use of FO controllers in haptic systems and provide a systematic analysis of this new control method in the light of the fundamental trade-off between the stability robustness and the transparency performance. FO controllers provide a promising generalization that allows one to better shape the frequency response of a system to achieve more favorable robustness and performance characteristics. In particular, the use of FO calculus in systems and control applications provides the user with an extra design variable, the order of differointegration, which can be tuned to improve the desired behavior of the overall system. We introduce a generalized FO nondimensionalized sampled-data model for the haptic system and study its frequency dependent behaviour. Then, we analyze the stability of this system with and without a human operator in the loop. Moreover, we experimentally verify the stability analysis and demonstrate that the experiments capture the essence of the stability behaviour between different differentiation orders. The passivity analysis is conducted for two cases: the first approach takes the environment model into account and ensures the passivity of the haptic system together with the virtual environment, while the second approach assumes the presence of a passive environment model in the control loop and introduces a controller to the closed-loop system that acts like a buffer between the haptic display and the virtual environment. The second approach is more suitable for complex environments as it investigates the passivity properties of the two-port haptic system together with a virtual coupler. After characterizing the stability boundaries for the FO haptic system, we analyse the performance of the system by studying the transparency performance of the haptic rendering with such controllers. In particular, we employ effective impedance analysis to decompose the closed-loop impedance of a haptic system into its parts and study the contribution of FO elements on the stiffness and damping rendering characteristics of the system. Finally, we apply the theoretical results to a novel haptic rendering scenario: haptic rendering of viscoelastic materials. A fractional order mathematical model for the human prostate tissue with history depended stress and deflection behavior, is chosen as the viscoelastic physical system to be rendered. The stress relaxation of the haptic rendering is verified against the experimental data, indicating a high fidelity rendering.

Fractional order calculus is a generalization of the familiar integer order calculus in that, it allows for differentiation/integration with orders of any real number. The use of fractional order calculus in systems and control applications provides the user an extra design variable, the order of differointegration, which can be tuned to improve the desired behavior of the overall system. We propose utilization of fractional order models/controllers in haptic systems and study the effect of fractional differentiation order on the stability robustness of the overall sampled-data system. Our results demonstrate that fractional calculus generalization has a significant impact on both the shape and area of stability region of a haptic system and inclusion of fractional order impedances may improve the stability robustness of haptic rendering. Our results also include experimental verification of the stability regions predicted by the theoretical analysis.