Below is a list of all relevant publications authored by Robotics Forum members.
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Journal articleTaniguchi T, Ugur E, Ogata T, et al., 2019,
Editorial: Machine Learning Methods for High-Level Cognitive Capabilities in Robotics
, FRONTIERS IN NEUROROBOTICS, Vol: 13, ISSN: 1662-5218 -
Conference paperEzzat A, Thakkar R, Kogkas A, et al., 2019,
Perceptions of surgeons and scrub nurses towards a novel eye-tracking based robotic scrub nurse platform
, International Surgical Congress of the Association-of-Surgeons-of-Great-Britain-and-Ireland (ASGBI), Publisher: WILEY, Pages: 81-82, ISSN: 0007-1323 -
Conference paperSaeedi S, Carvalho EDC, Li W, et al., 2019,
Characterizing visual localization and mapping datasets
, 2019 International Conference on Robotics and Automation (ICRA), Publisher: Institute of Electrical and Electronics Engineers, ISSN: 1050-4729Benchmarking mapping and motion estimation algorithms is established practice in robotics and computer vision. As the diversity of datasets increases, in terms of the trajectories, models, and scenes, it becomes a challenge to select datasets for a given benchmarking purpose. Inspired by the Wasserstein distance, this paper addresses this concern by developing novel metrics to evaluate trajectories and the environments without relying on any SLAM or motion estimation algorithm. The metrics, which so far have been missing in the research community, can be applied to the plethora of datasets that exist. Additionally, to improve the robotics SLAM benchmarking, the paper presents a new dataset for visual localization and mapping algorithms. A broad range of real-world trajectories is used in very high-quality scenes and a rendering framework to create a set of synthetic datasets with ground-truth trajectory and dense map which are representative of key SLAM applications such as virtual reality (VR), micro aerial vehicle (MAV) flight, and ground robotics.
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Conference paperBujanca M, Gafton P, Saeedi S, et al., 2019,
SLAMBench 3.0: Systematic automated reproducible evaluation of SLAM systems for robot vision challenges and scene understanding
, 2019 International Conference on Robotics and Automation (ICRA), Publisher: Institute of Electrical and Electronics Engineers, ISSN: 1050-4729As the SLAM research area matures and the number of SLAM systems available increases, the need for frameworks that can objectively evaluate them against prior work grows. This new version of SLAMBench moves beyond traditional visual SLAM, and provides new support for scene understanding and non-rigid environments (dynamic SLAM). More concretely for dynamic SLAM, SLAMBench 3.0 includes the first publicly available implementation of DynamicFusion, along with an evaluation infrastructure. In addition, we include two SLAM systems (one dense, one sparse) augmented with convolutional neural networks for scene understanding, together with datasets and appropriate metrics. Through a series of use-cases, we demonstrate the newly incorporated algorithms, visulation aids and metrics (6 new metrics, 4 new datasets and 5 new algorithms).
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Conference paperAvery J, Runciman M, Darzi A, et al., 2019,
Shape sensing of variable stiffness soft robots using electrical impedance tomography
, International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 9066-9072, ISSN: 1050-4729Soft robotic systems offer benefits over traditional rigid systems through reduced contact trauma with soft tissues and by enabling access through tortuous paths in minimally invasive surgery. However, the inherent deformability of soft robots places both a greater onus on accurate modelling of their shape, and greater challenges in realising intraoperative shape sensing. Herein we present a proprioceptive (self-sensing) soft actuator, with an electrically conductive working fluid. Electrical impedance measurements from up to six electrodes enabled tomographic reconstructions using Electrical Impedance Tomography (EIT). A new Frequency Division Multiplexed (FDM) EIT system was developed capable of measurements of 66 dB SNR with 20 ms temporal resolution. The concept was examined in two two-degree-of-freedom designs: a hydraulic hinged actuator and a pneumatic finger actuator with hydraulic beams. Both cases demonstrated that impedance measurements could be used to infer shape changes, and EIT images reconstructed during actuation showed distinct patterns with respect to each degree of freedom (DOF). Whilst there was some mechanical hysteresis observed, the repeatability of the measurements and resultant images was high. The results show the potential of FDM-EIT as a low-cost, low profile shape sensor in soft robots.
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Journal articleRunciman M, Darzi A, Mylonas G, 2019,
Soft robotics in minimally invasive surgery
, Soft Robotics, Vol: 6, Pages: 423-443, ISSN: 2169-5172Soft robotic devices have desirable traits for applications in minimally invasive surgery (MIS) but many interdisciplinary challenges remain unsolved. To understand current technologies, we carried out a keyword search using the Web of Science and Scopus databases, applied inclusion and exclusion criteria, and compared several characteristics of the soft robotic devices for MIS in the resulting articles. There was low diversity in the device designs and a wide-ranging level of detail regarding their capabilities. We propose a standardised comparison methodology to characterise soft robotics for various MIS applications, which will aid designers producing the next generation of devices.
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Conference paperFalck F, Doshi S, Smuts N, et al., 2019,
Human-centered manipulation and navigation with robot DE NIRO
Social assistance robots in health and elderly care have the potential tosupport and ease human lives. Given the macrosocial trends of aging andlong-lived populations, robotics-based care research mainly focused on helpingthe elderly live independently. In this paper, we introduce Robot DE NIRO, aresearch platform that aims to support the supporter (the caregiver) and alsooffers direct human-robot interaction for the care recipient. Augmented byseveral sensors, DE NIRO is capable of complex manipulation tasks. It reliablyinteracts with humans and can autonomously and swiftly navigate throughdynamically changing environments. We describe preliminary experiments in ademonstrative scenario and discuss DE NIRO's design and capabilities. We putparticular emphases on safe, human-centered interaction procedures implementedin both hardware and software, including collision avoidance in manipulationand navigation as well as an intuitive perception stack through speech and facerecognition.
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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,
Probabilistic real-time user posture tracking for personalized robot-assisted dressing
, IEEE Transactions on Robotics, Vol: 35, Pages: 873-888, ISSN: 1552-3098Robotic 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.
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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: arXivWe 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.
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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: 0302-9743While 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/.
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Conference paperAlAttar A, Rouillard L, Kormushev P, 2019,
Autonomous air-hockey playing cobot using optimal control and vision-based Bayesian tracking
, Towards Autonomous Robotic Systems, Publisher: Springer, ISSN: 0302-9743This 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.
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Journal articleClark A, Rojas N, 2019,
Assessing the performance of variable stiffness continuum structures of large diameter
, IEEE Robotics and Automation Letters, Vol: 4, Pages: 2455-2462, ISSN: 2377-3766Variable 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.
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Conference paperBagga S, Maurer B, Miller T, et al., 2019,
instruMentor: An Interactive Robot for Musical Instrument Tutoring
, Towards Autonomous Robotic Systems Conference, Publisher: Springer International Publishing, Pages: 303-315, ISSN: 0302-9743 -
Conference paperNanayakkara V, Sornkaran N, Wegiriya H, et al., 2019,
A method to estimate the oblique arch folding axis for thumb assistive devices
, 20th Towards Autonomous Robotic Systems Conference, Publisher: Springer Verlag, Pages: 28-40, ISSN: 0302-9743People 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.
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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.
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Conference paperPatel N, Kogkas A, Ben Glover AD, et al., 2019,
EYE GAZE-CONTROLLED ROBOTIC FLEXIBLE ENDOSCOPY: A FEASIBILITY STUDY
, Annual Meeting of the British-Society-of-Gastroenterology (BSG), Publisher: BMJ PUBLISHING GROUP, Pages: A38-A39, ISSN: 0017-5749- Author Web Link
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Conference paperClark AB, Rojas N, 2019,
Stiffness-tuneable limb segment with flexible spine for malleable robots
, 2019 International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 3969-3975, ISSN: 2577-087XRobotic 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°.
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Journal articleCully A, Demiris Y, 2019,
Online knowledge level tracking with data-driven student models and collaborative filtering
, IEEE Transactions on Knowledge and Data Engineering, Vol: 32, Pages: 2000-2013, ISSN: 1041-4347Intelligent 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.
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Conference paperMatheson E, Watts T, Secoli R, et al., 2019,
Cyclic motion control for programmable bevel-tip needles 3D steering: a simulation study
, ROBIO - IEEE International Conference on Robotics and Biomimetics, Publisher: IEEEFlexible, 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.
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