Below is a list of all relevant publications authored by Robotics Forum members.
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Conference paperFathi J, Vrielink TJCO, Runciman MS, et al., 2019,
A Deployable Soft Robotic Arm with Stiffness Modulation for Assistive Living Applications, International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 1479-1485, ISSN: 1050-4729
Journal articleZhang F, Cully A, Demiris Y, 2019,
Robotic solutions to dressing assistance have the potential to provide tremendous support for elderly and disabled people. However, unexpected user movements may lead to dressing failures or even pose a risk to the user. Tracking such user movements with vision sensors is challenging due to severe visual occlusions created by the robot and clothes. In this paper, we propose a probabilistic tracking method using Bayesian networks in latent spaces, which fuses robot end-effector positions and force information to enable cameraless and real-time estimation of the user postures during dressing. The latent spaces are created before dressing by modeling the user movements with a Gaussian process latent variable model, taking the user’s movement limitations into account. We introduce a robot-assisted dressing system that combines our tracking method with hierarchical multitask control to minimize the force between the user and the robot. The experimental results demonstrate the robustness and accuracy of our tracking method. The proposed method enables the Baxter robot to provide personalized dressing assistance in putting on a sleeveless jacket for users with (simulated) upper-body impairments.
Conference paperTavakoli A, Levdik V, Islam R, et al., 2019,
Exploring Restart Distributions, Montréal, Canada, The Fourth Multidisciplinary Conference on Reinforcement Learning and Decision Making, Publisher: arXiv
We consider the generic approach of using an experience memory to help exploration by adapting a restart distribution. That is, given the capacity to reset the state with those corresponding to the agent's past observations, we help exploration by promoting faster state-space coverage via restarting the agent from a more diverse set of initial states, as well as allowing it to restart in states associated with significant past experiences. This approach is compatible with both on-policy and off-policy methods. However, a caveat is that altering the distribution of initial states could change the optimal policies when searching within a restricted class of policies. To reduce this unsought learning bias, we evaluate our approach in deep reinforcement learning which benefits from the high representational capacity of deep neural networks. We instantiate three variants of our approach, each inspired by an idea in the context of experience replay. Using these variants, we show that performance gains can be achieved, especially in hard exploration problems.
Conference paperAlAttar A, Rouillard L, Kormushev P, 2019,
This paper presents a novel autonomous air-hockey playing collaborative robot (cobot) that provides human-like gameplay against human opponents. Vision-based Bayesian tracking of the puck and striker are used in an Analytic Hierarchy Process (AHP)-based probabilistic tactical layer for high-speed perception. The tactical layer provides commands for an active control layer that controls the Cartesian position and yaw angle of a custom end effector. The active layer uses optimal control of the cobot’s posture inside the task nullspace. The kinematic redundancy is resolved using a weighted Moore-Penrose pseudo-inversion technique. Experiments with human players show high-speed human-like gameplay with potential applications in the growing field of entertainment robotics.
Conference paperFalck F, Larppichet K, Kormushev P, 2019,
DE VITO: A dual-arm, high degree-of-freedom, lightweight, inexpensive, passive upper-limb exoskeleton for robot teleoperation, TAROS: Annual Conference Towards Autonomous Robotic Systems, Publisher: Springer, ISSN: 0302-9743
While robotics has made significant advances in perception, planning and control in recent decades, the vast majority of tasks easily completed by a human, especially acting in dynamic, unstructured environments, are far from being autonomously performed by a robot. Teleoperation, remotely controlling a slave robot by a human operator, can be a realistic, complementary transition solution that uses the motion intelligence of a human in complex tasks while exploiting the robot’s autonomous reliability and precision in less challenging situations.We introduce DE VITO, a seven degree-of-freedom, dual-arm upper-limb exoskeleton that passively measures the pose of a human arm. DE VITO is a lightweight, simplistic and energy-efficient design with a total material cost of at least an order of magnitude less than previous work. Given the estimated human pose, we implement both joint and Cartesian space kinematic control algorithms and present qualitative experimental results on various complex manipulation tasks teleoperating Robot DE NIRO, a research platform for mobile manipulation, that demonstrate the functionality of DE VITO. We provide the CAD models, open-source code and supplementary videos of DE VITO at http://www.imperial.ac.uk/robot-intelligence/robots/de_vito/.
Journal articleClark A, Rojas N, 2019,
Variable stiffness continuum structures of large diameters are suitable for high-capability robots, such as in industrial practices where high loads and human–robot interaction are expected. Existing variable stiffness technologies have focused on application as medical manipulators, and as such have been limited to small diameter designs ( $\sim$ 15 mm). Various performance metrics have been presented for continuum structures thus far, focusing on force resistance, but no universal testing methodology for continuum structures that encapsulates their overall performance has been provided. This letter presents five individual qualities that can be experimentally quantified to establish the overall performance capability of a design with respect to its use as a variable stiffness continuum manipulator. Six large diameter ( $>$ 40 mm) continuum structures are developed following both conventional (granular and layer jamming) and novel (hybrid designs and structurally supported layer jamming) approaches and are compared using the presented testing methodology. The development of the continuum structures is discussed, and a detailed insight into the tested quality selection and experimental methodology is presented. Results of experiments demonstrate the suitability of the proposed approach for assessing variable stiffness continuum capability across the design.
Journal articleLu Q, Rojas N, 2019,
Contact models for soft fingertips are able to precisely computedeformation when information about contact forces and object position is known, thus improving the traditional soft finger contact model. However, the functionality of these approaches for the study of in-hand manipulation with robot hands has been shown to be limited, since the location of the manipulated object is uncertain due to compliance and closed-loop constraints. This paper presents a novel, tractable approach for contact modelling of soft fingertips in within-hand dexterous manipulation settings. The proposed method is based on a relaxation of the kinematic equivalent of point contact with friction, modelling the interaction between fingertips and objects as joints with clearances rather than ideal instances, and then approximating clearances via affine arithmetic to facilitate computation. These ideas are introduced using planar manipulation to aid discussion, and are used to predict the reachable workspace of a two-fingered robot hand with fingertips of different hardness and geometry. Numerical and empirical experiments are conducted to analyse the effects of soft fingertips on manipulation operability; results demonstrate the functionality of the proposed approach, as well as a tradeoff between hardness and depth in soft fingertips to achieve better manipulation performance of dexterous robot hands.
Conference paperNanayakkara V, Sornkaran N, Wegiriya H, et al., 2019,
People who use the thumb in repetitive manipulation tasks are likelyto develop thumb related impairments from excessive loading at the base jointsof the thumb. Biologically informed wearable robotic assistive mechanisms canprovide viable solutions to prevent occurring such injuries. This paper tests thehypothesis that an external assistive force at the metacarpophalangeal joint willbe most effective when applied perpendicular to the palm folding axis in termsof maximizing the contribution at the thumb-tip as well as minimizing the pro-jections on the vulnerable base joints of the thumb. Experiments conducted usinghuman subjects validated the predictions made by a simplified kinematic modelof the thumb that includes a foldable palm, showing that: 1) the palm folding an-gle varies from 71.5◦to 75.3◦(from the radial axis in the coronal plane) for thefour thumb-finger pairs and 2) the most effective assistive force direction (fromthe ulnar axis in the coronal plane) at the MCP joint is in the range 0◦<ψ<30◦for the four thumb-finger pairs. These findings provide design guidelines for handassistive mechanisms to maximize the efficacy of thumb external assistance.
Conference paperCheung YH, Baron N, Rojas N, 2019,
Full-rotation singularity-safe workspace for kinematically redundant parallel robots, 20th Towards Autonomous Robotic Systems Conference, Publisher: Springer Verlag, ISSN: 0302-9743
This paper introduces and computes a novel type of work-space for kinematically redundant parallel robots that defines the regionin which the end-effector can make full rotations without coming close tosingular configurations; it departs from the traditional full-rotation dex-terous workspace, which considers full rotations without encounteringsingularities but does not take into account the performance problemsresulting from closeness to these locations. Kinematically redundant ar-chitectures have the advantage of being able to be reconfigured withoutchanging the pose of the end-effector, thus being capable of avoidingsingularities and being suitable for applications where high dexterityis required. Knowing the workspace of these robots in which the end-effector is able to complete full, smooth rotations is a key design aspectto improve performance; however, since this singularity-safe workspaceis generally small, or even non-existent, in most parallel manipulators,its characterisation and calculation have not received attention in theliterature. The proposed workspace for kinematically redundant robotsis introduced using a planar parallel architecture as a case study; the for-mulation works by treating the manipulator as two halves, calculatingthe full-rotation workspace of the end-effector for each half whilst ensur-ing singularity conditions are not approached or met, and then findingthe intersection of both regions. The method is demonstrated ontwoexample robot instances, and a numerical analysis is also carried out asa comparison.
Conference paperBagga S, Maurer B, Miller T, et al., 2019,
Conference paperWang R, Ciliberto C, Amadori P, et al., 2019,
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation, Thirty-sixth International Conference on Machine Learning, Publisher: Proceedings of International Conference on Machine Learning (ICML-2019)
We consider the problem of imitation learning from a finite set of experttrajectories, without access to reinforcement signals. The classical approachof extracting the expert's reward function via inverse reinforcement learning,followed by reinforcement learning is indirect and may be computationallyexpensive. Recent generative adversarial methods based on matching the policydistribution between the expert and the agent could be unstable duringtraining. We propose a new framework for imitation learning by estimating thesupport of the expert policy to compute a fixed reward function, which allowsus to re-frame imitation learning within the standard reinforcement learningsetting. We demonstrate the efficacy of our reward function on both discreteand continuous domains, achieving comparable or better performance than thestate of the art under different reinforcement learning algorithms.
Conference paperPatel N, Kogkas A, Ben Glover AD, et al., 2019,
Conference paperClark AB, Rojas N, 2019,
Robotic arms built from stiffness-adjustable, con-tinuously bending segments serially connected with revolutejoints have the ability to change their mechanical architectureand workspace, thus allowing high flexibility and adaptation todifferent tasks with less than six degrees of freedom, a conceptthat we call malleable robots. Known stiffening mechanismsmay be used to implement suitable links for these novel roboticmanipulators; however, these solutions usually show a reducedperformance when bending due to structural deformation. Byincluding an inner support structure this deformation can beminimised, resulting in an increased stiffening performance.This paper presents a new multi-material spine-inspired flexiblestructure for providing support in stiffness-controllable layer-jamming-based robotic links of large diameter. The proposedspine mechanism is highly movable with type and range ofmotions that match those of a robotic link using solely layerjamming, whilst maintaining a hollow and light structure. Themechanics and design of the flexible spine are explored, anda prototype of a link utilising it is developed and comparedwith limb segments based on granular jamming and layerjamming without support structure. Results of experimentsverify the advantages of the proposed design, demonstratingthat it maintains a constant central diameter across bendingangles and presents an improvement of more than 203% ofresisting force at 180°.
Journal articleCully A, Demiris Y, 2019,
Intelligent Tutoring Systems are promising tools for delivering optimal and personalised learning experiences to students. A key component for their personalisation is the student model, which infers the knowledge level of the students to balance the difficulty of the exercises. While important advances have been achieved, several challenges remain. In particular, the models should be able to track in real-time the evolution of the students' knowledge levels. These evolutions are likely to follow different profiles for each student, while measuring the exact knowledge level remains difficult given the limited and noisy information provided by the interactions. This paper introduces a novel model that addresses these challenges with three contributions: 1) the model relies on Gaussian Processes to track online the evolution of the student's knowledge level over time, 2) it uses collaborative filtering to rapidly provide long-term predictions by leveraging the information from previous users, and 3) it automatically generates abstract representations of knowledge components via automatic relevance determination of covariance matrices. The model is evaluated on three datasets, including real users. The results demonstrate that the model converges to accurate predictions in average 4 times faster than the compared methods.
Conference paperMatheson E, Watts T, Secoli R, et al., 2019,
Flexible, steerable, soft needles are desirable inMinimally Invasive Surgery to achieve complex trajectorieswhile maintaining the benefits of percutaneous interventioncompared to open surgery. One such needle is the multi-segmentProgrammable Bevel-tip Needle (PBN), which is inspired by themechanical design of the ovipositor of certain wasps. PBNscan steer in 3D whilst minimizing the force applied to thesurrounding substrate, due to the cyclic motion of the segments.Taking inspiration also from the control strategy of the wasp toperform insertions and lay their eggs, this paper presents thedesign of a cyclic controller that can steer a PBN to produce adesired trajectory in 3D. The performance of the controller isdemonstrated in simulation in comparison to that of a directcontroller without cyclic motion. It is shown that, while thesame steering curvatures can be attained by both controllers,the time taken to achieve the configuration is longer for thecyclic controller, leading to issues of potential under-steeringand longer insertion times.
Journal articleBaron N, Philippides A, Rojas N, 2019,
This paper presents a novel kinematically redundant planar parallel robot manipulator, which has full rotatability. The proposed robot manipulator has an architecture that corresponds to a fundamental truss, meaning that it does not contain internal rigid structures when the actuators are locked. This also implies that its rigidity is not inherited from more general architectures or resulting from the combination of other fundamental structures. The introduced topology is a departure from the standard 3-RPR (or 3-RRR) mechanism on which most kinematically redundant planar parallel robot manipulators are based. The robot manipulator consists of a moving platform that is connected to the base via two RRR legs and connected to a ternary link, which is joined to the base by a passive revolute joint, via two other RRR legs. The resulting robot mechanism is kinematically redundant, being able to avoid the production of singularities and having unlimited rotational capability. The inverse and forward kinematics analyses of this novel robot manipulator are derived using distance-based techniques, and the singularity analysis is performed using a geometric method based on the properties of instantaneous centers of rotation. An example robot mechanism is analyzed numerically and physically tested; and a test trajectory where the end effector completes a full cycle rotation is reported. A link to an online video recording of such a capability, along with the avoidance of singularities and a potential application, is also provided.
Journal articleKormushev P, Ugurlu B, Caldwell DG, et al., 2019,
Modern humanoid robots include not only active compliance but also passive compliance. Apart from improved safety and dependability, availability of passive elements, such as springs, opens up new possibilities for improving the energy efficiency. With this in mind, this paper addresses the challenging open problem of exploiting the passive compliance for the purpose of energy efficient humanoid walking. To this end, we develop a method comprising two parts: an optimization part that finds an optimal vertical center-of-mass trajectory, and a walking pattern generator part that uses this trajectory to produce a dynamically-balanced gait. For the optimization part, we propose a reinforcement learning approach that dynamically evolves the policy parametrization during the learning process. By gradually increasing the representational power of the policy parametrization, it manages to find better policies in a faster and computationally efficient way. For the walking generator part, we develop a variable-center-of-mass-height ZMP-based bipedal walking pattern generator. The method is tested in real-world experiments with the bipedal robot COMAN and achieves a significant 18% reduction in the electric energy consumption by learning to efficiently use the passive compliance of the robot.
Conference paperBai G, Rojas N, 2019,
Self-adaptive monolithic anthropomorphic finger with teeth-guided compliant cross-four-bar joints for underactuated hands, 2018 IEEE-RAS International Conference on Humanoid Robots (Humanoids), Publisher: IEEE
This paper presents a novel approach for modelingone-degree-of-freedom human metacarpophalangeal/ interpha-langeal joints based on a teeth-guided compliant cross-four-barlinkage. The proposed model allows developing self-adaptiveanthropomorphic fingers able to be 3D printed in a singlestep without any accessories, except for simple tendon wiringafter the printing process, using basic single-material additivemanufacturing. Teeth-guided compliant cross-four-bar linkagesas finger joints not only provide monolithic fabrication withoutassembly but also increase precision of anthropomorphic robotfingers by removing nonlinear characteristics, thus reducing thecomplexity of control for delicate grasping. Kinematic analysisof the proposed compliant finger joints is detailed and nonlinearfinite element analysis results demonstrating their advantagesare reported. A two-fingered underactuated hand with teeth-guided compliant cross-four-bar joints is also developed andqualitative discussion on grasping is conducted.
Conference paperWang M-Y, Kogkas AA, Darzi A, et al., 2019,
Patients suffering from quadriplegia have limited body motion which prevents them from performing daily activities. We have developed an assistive robotic system with an intuitive free-view gaze interface. The user's point of regard is estimated in 3D space while allowing free head movement and is combined with object recognition and trajectory planning. This framework allows the user to interact with objects using fixations. Two operational modes have been implemented to cater for different eventualities. The automatic mode performs a pre-defined task associated with a gaze-selected object, while the manual mode allows gaze control of the robot's end-effector position on the user's frame of reference. User studies reported effortless operation in automatic mode. A manual pick and place task achieved a success rate of 100% on the users' first attempt.
Conference paperVrielink TJCO, Puyal JG-B, Kogkas A, et al., 2019,
Flexible endoscopy is a routinely performed procedure that has predominantly remained unchanged for decades despite its many challenges. This paper introduces a novel, more intuitive and ergonomic platform that can be used with any flexible endoscope, allowing easier navigation and manipulation. A standard endoscope is robotized and a gaze control system based on eye-tracking is developed and implemented, allowing hands-free manipulation. The system characteristics and step response has been evaluated using visual servoing. Further, the robotized system has been compared with a manually controlled endoscope during a user study. The users (n=11) showed a preference for the gaze controlled endoscope and a lower task load when the task was performed with the gaze control. In addition, gaze control was related to a higher success rate and a lower time to perform the task. The results presented validate the system's technical performance and demonstrate the intuitiveness of hands-free gaze control in flexible endoscopy.
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