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  • Conference paper
    Wang K, Marsh DM, Saputra RP, Chappell D, Jiang Z, Kon B, Kormushev Pet al., 2020,

    Design and control of SLIDER: an ultra-lightweight, knee-less, low-cost bipedal walking robot

    , Las Vegas, USA, International Conference on Intelligence Robots and Systems (IROS)

    Most state-of-the-art bipedal robots are designedto be highly anthropomorphic and therefore possess legs withknees. Whilst this facilitates more human-like locomotion, thereare implementation issues that make walking with straight ornear-straight legs difficult. Most bipedal robots have to movewith a constant bend in the legs to avoid singularities at theknee joints, and to keep the centre of mass at a constant heightfor control purposes. Furthermore, having a knee on the legincreases the design complexity as well as the weight of the leg,hindering the robot’s performance in agile behaviours such asrunning and jumping.We present SLIDER, an ultra-lightweight, low-cost bipedalwalking robot with a novel knee-less leg design. This nonanthropomorphic straight-legged design reduces the weight ofthe legs significantly whilst keeping the same functionality asanthropomorphic legs. Simulation results show that SLIDER’slow-inertia legs contribute to less vertical motion in the centerof mass (CoM) than anthropomorphic robots during walking,indicating that SLIDER’s model is closer to the widely usedInverted Pendulum (IP) model. Finally, stable walking onflat terrain is demonstrated both in simulation and in thephysical world, and feedback control is implemented to addresschallenges with the physical robot.

  • Journal article
    AlAttar A, Kormushev P, 2020,

    Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions

    , Robotics, Vol: 9, Pages: 1-12, ISSN: 2218-6581
  • Journal article
    Cursi F, Mylonas GP, Kormushev P, 2020,

    Adaptive kinematic modelling for multiobjective control of a redundant surgical robotic tool

    , Robotics, Vol: 9, Pages: 68-68, ISSN: 2218-6581

    Accurate kinematic models are essential for effective control of surgical robots. For tendon driven robots, which are common for minimally invasive surgery, the high nonlinearities in the transmission make modelling complex. Machine learning techniques are a preferred approach to tackle this problem. However, surgical environments are rarely structured, due to organs being very soft and deformable, and unpredictable, for instance, because of fluids in the system, wear and break of the tendons that lead to changes of the system’s behaviour. Therefore, the model needs to quickly adapt. In this work, we propose a method to learn the kinematic model of a redundant surgical robot and control it to perform surgical tasks both autonomously and in teleoperation. The approach employs Feedforward Artificial Neural Networks (ANN) for building the kinematic model of the robot offline, and an online adaptive strategy in order to allow the system to conform to the changing environment. To prove the capabilities of the method, a comparison with a simple feedback controller for autonomous tracking is carried out. Simulation results show that the proposed method is capable of achieving very small tracking errors, even when unpredicted changes in the system occur, such as broken joints. The method proved effective also in guaranteeing accurate tracking in teleoperation.

  • Journal article
    Escribano Macias J, Goldbeck N, Hsu P-Y, Angeloudis P, Ochieng Wet al., 2020,

    Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles

    , OR SPECTRUM, ISSN: 0171-6468
  • Journal article
    Falck F, Doshi S, Tormento M, Nersisyan G, Smuts N, Lingi J, Rants K, Saputra RP, Wang K, Kormushev Pet al., 2020,

    Robot DE NIRO: a human-centered, autonomous, mobile research platform for cognitively-enhanced manipulation

    , Frontiers in Robotics and AI, Vol: A17, ISSN: 2296-9144

    We introduceRobot DE NIRO, an autonomous, collaborative, humanoid robot for mobilemanipulation. We built DE NIRO to perform a wide variety of manipulation behaviors, with afocus on pick-and-place tasks. DE NIRO is designed to be used in a domestic environment,especially in support of caregivers working with the elderly. Given this design focus, DE NIRO caninteract naturally, reliably, and safely with humans, autonomously navigate through environmentson command, intelligently retrieve or move target objects, and avoid collisions efficiently. Wedescribe DE NIRO’s hardware and software, including an extensive vision sensor suite of 2Dand 3D LIDARs, a depth camera, and a 360-degree camera rig; two types of custom grippers;and a custom-built exoskeleton called DE VITO. We demonstrate DE NIRO’s manipulationcapabilities in three illustrative challenges: First, we have DE NIRO perform a fetch-an-objectchallenge. Next, we add more cognition to DE NIRO’s object recognition and grasping abilities,confronting it with small objects of unknown shape. Finally, we extend DE NIRO’s capabilitiesinto dual-arm manipulation of larger objects. We put particular emphasis on the features thatenable DE NIRO to interact safely and naturally with humans. Our contribution is in sharinghow a humanoid robot with complex capabilities can be designed and built quickly with off-the-shelf hardware and open-source software. Supplementary material including our code, adocumentation, videos and the CAD models of several hardware parts are openly availableavailable at

  • Conference paper
    Flageat M, Cully A, 2020,

    Fast and stable MAP-Elites in noisy domains using deep grids

    , 2020 Conference on Artificial Life, Publisher: Massachusetts Institute of Technology, Pages: 273-282

    Quality-Diversity optimisation algorithms enable the evolutionof collections of both high-performing and diverse solutions.These collections offer the possibility to quickly adapt andswitch from one solution to another in case it is not workingas expected. It therefore finds many applications in real-worlddomain problems such as robotic control. However, QD algo-rithms, like most optimisation algorithms, are very sensitive touncertainty on the fitness function, but also on the behaviouraldescriptors. Yet, such uncertainties are frequent in real-worldapplications. Few works have explored this issue in the spe-cific case of QD algorithms, and inspired by the literature inEvolutionary Computation, mainly focus on using samplingto approximate the ”true” value of the performances of a solu-tion. However, sampling approaches require a high number ofevaluations, which in many applications such as robotics, canquickly become impractical.In this work, we propose Deep-Grid MAP-Elites, a variantof the MAP-Elites algorithm that uses an archive of similarpreviously encountered solutions to approximate the perfor-mance of a solution. We compare our approach to previouslyexplored ones on three noisy tasks: a standard optimisationtask, the control of a redundant arm and a simulated Hexapodrobot. The experimental results show that this simple approachis significantly more resilient to noise on the behavioural de-scriptors, while achieving competitive performances in termsof fitness optimisation, and being more sample-efficient thanother existing approaches.

  • Conference paper
    Lu Q, Baron N, Clark A, Rojas Net al., 2020,

    The RUTH Gripper: systematic object-invariant prehensile in-hand manipulation via reconfigurable underactuation

    , Robotics: Science and Systems, Publisher: RSS

    We introduce a reconfigurable underactuated robothand able to perform systematic prehensile in-hand manipu-lations regardless of object size or shape. The hand utilisesa two-degree-of-freedom five-bar linkage as the palm of thegripper, with three three-phalanx underactuated fingers—jointlycontrolled by a single actuator—connected to the mobile revolutejoints of the palm. Three actuators are used in the robot handsystem, one for controlling the force exerted on objects by thefingers and two for changing the configuration of the palm.This novel layout allows decoupling grasping and manipulation,facilitating the planning and execution of in-hand manipulationoperations. The reconfigurable palm provides the hand withlarge grasping versatility, and allows easy computation of amap between task space and joint space for manipulation basedon distance-based linkage kinematics. The motion of objects ofdifferent sizes and shapes from one pose to another is thenstraightforward and systematic, provided the objects are keptgrasped. This is guaranteed independently and passively by theunderactuated fingers using a custom tendon routing method,which allows no tendon length variation when the relative fingerbase position changes with palm reconfigurations. We analysethe theoretical grasping workspace and manipulation capabilityof the hand, present algorithms for computing the manipulationmap and in-hand manipulation planning, and evaluate all theseexperimentally. Numerical and empirical results of several ma-nipulation trajectories with objects of different size and shapeclearly demonstrate the viability of the proposed concept.

  • Journal article
    Kinross JM, Mason SE, Mylonas G, Darzi Aet al., 2020,

    Next-generation robotics in gastrointestinal surgery

    , Nature Reviews Gastroenterology and Hepatology, Vol: 17, Pages: 430-440, ISSN: 1759-5045

    The global numbers of robotic gastrointestinal surgeries are increasing. However, the evidence base for robotic gastrointestinal surgery does not yet support its widespread adoption or justify its cost. The reasons for its continued popularity are complex, but a notable driver is the push for innovation — robotic surgery is seen as a compelling solution for delivering on the promise of minimally invasive precision surgery — and a changing commercial landscape delivers the promise of increased affordability. Novel systems will leverage the robot as a data-driven platform, integrating advances in imaging, artificial intelligence and machine learning for decision support. However, if this vision is to be realized, lessons must be heeded from current clinical trials and translational strategies, which have failed to demonstrate patient benefit. In this Perspective, we critically appraise current research to define the principles on which the next generation of gastrointestinal robotics trials should be based. We also discuss the emerging commercial landscape and define existing and new technologies.

  • Journal article
    Baron N, Philippides A, Rojas N, 2020,

    On the false positives and false negatives of the Jacobian matrix in kinematically redundant parallel mechanisms

    , IEEE Transactions on Robotics, Vol: 36, ISSN: 1552-3098

    The Jacobian matrix is a highly popular tool for the control and performance analysis of closed-loop robots. Its usefulness in parallel mechanisms is certainly apparent, and its application to solve motion planning problems, or other higher level questions, has been seldom queried, or limited to non-redundant systems. In this paper, we discuss the shortcomings of the use of the Jacobian matrix under redundancy, in particular when applied to kinematically redundant parallel architectures with non-serially connected actuators. These architectures have become fairly popular recently as they allow the end-effector to achieve full rotations, which is an impossible task with traditional topologies. The problems with the Jacobian matrix in these novel systems arise from the need to eliminate redundant variables when forming it, resulting in both situations where the Jacobian incorrectly identifies singularities (false positive), and where it fails to identify singularities (false negative). These issues have thus far remained unaddressed in the literature. We highlight these limitations herein by demonstrating several cases using numerical examples of both planar and spatial architectures.

  • Journal article
    Saracino A, Oude Vrielink TJC, Menciassi A, Sinibaldi E, Mylonas GPet al., 2020,

    Haptic intracorporeal palpation using a cable-driven parallel robot: a user study.

    , IEEE Trans Biomed Eng, Vol: PP

    OBJECTIVE: Intraoperative palpation is a surgical gesture jeopardized by the lack of haptic feedback which affects robotic minimally invasive surgery. Restoring the force reflection in teleoperated systems may improve both surgeons' performance and procedures' outcome. METHODS: A force-based sensing approach was developed, based on a cable-driven parallel manipulator with anticipated seamless and low-cost integration capabilities in teleoperated robotic surgery. No force sensor on the end-effector is used, but tissue probing forces are estimated from measured cable tensions. A user study involving surgical trainees (n=22) was conducted to experimentally evaluate the platform in two palpation-based test-cases on silicone phantoms. Two modalities were compared: visual feedback alone and both visual + haptic feedbacks available at the master site. RESULTS: Surgical trainees' preference for the modality providing both visual and haptic feedback is corroborated by both quantitative and qualitative metrics. Hard nodules detection sensitivity improves (94.35 ± 9.1% vs 76.09 ± 19.15 % for visual feedback alone), while also exerting smaller forces (4.13 ± 1.02 N vs 4.82 ± 0.81 N for visual feedback alone) on the phantom tissues. At the same time, the subjective perceived workload decreases. CONCLUSION: Tissue-probe contact forces are estimated in a low cost and unique way, without the need of force sensors on the end-effector. Haptics demonstrated an improvement in the tumor detection rate, a reduction of the probing forces, and a decrease in the perceived workload for the trainees. SIGNIFICANCE: Relevant benefits are demonstrated from the usage of combined cable-driven parallel manipulators and haptics during robotic minimally invasive procedures. The translation of robotic intraoperative palpation to clinical practice could improve the detection and dissection of cancer nodules.

  • Conference paper
    Shen M, Clark A, Rojas N, 2020,

    A scalable variable stiffness revolute joint based on layer jamming for robotic exoskeletons

    , Towards Autonomous Robotic Systems Conference ( TAROS ) 2020, Publisher: Springer Verlag, ISSN: 0302-9743

    Robotic exoskeletons have been a focal point of research dueto an ever-increasing ageing population, longer life expectancy, and adesire to further improve the existing capabilities of humans. However,their effectiveness is often limited, with strong rigid structures poorlyinterfacing with humans and soft flexible mechanisms providing limitedforces. In this paper, a scalable variable stiffness revolute jointis pro-posed to overcome this problem. By using layer jamming, the jointhasthe ability to stiffen or soften for different use cases. A theoretical and ex-perimental study of maximum stiffness with size was conductedto deter-mine the suitability and scalablity of this technology. Three sizes (25 mm,18.75 mm, 12.5 mm diameter) of the joint were developed and evaluated.Results indicate that this technology is most suitable for use in humanfingers, as the prototypes demonstrate a sufficient torque (0.054 Nm) tosupport finger movement.

  • Conference paper
    Wang J, Lu Q, Clark A, Rojas Net al., 2020,

    A passively complaint idler mechanism for underactuated dexterous grippers with dynamic tendon routing

    , Towards Autonomous Robotic Systems Conference (TAROS ) 2020, Publisher: Springer Verlag, ISSN: 0302-9743

    n the field of robotic hands, tendon actuation is one of themost common ways to control self-adaptive underactuated fingers thanksto its compact size. Either differential or direct drive mechanisms areusually used in these systems to perform synchronised grasping using asingle actuator. However, synchronisation problems arise in underactu-ated grippers whose position of proximal joints varies with time to per-form manipulation operations, as this results in a tendon-driven systemwith dynamic anchor pulleys. This paper introduces a novel passivelycomplaint idler mechanism to avoid unsynchronisation in grippers witha dynamic multi-tendon routing system, such that adequate graspingcontact forces are kept under changes in the proximal joints’ positions.A re-configurable palm underactuated dexterous gripper is used as acase study, with the performance of the proposed compliant idler systembeing evaluated and compared through a contact force analysis duringrotation and translation in-hand manipulation tasks. Experiment resultsclearly demonstrate the ability of the mechanism to synchronise a dy-namic tendon routing gripper. A video summarising experiments andfindings can be found at

  • Journal article
    Baron N, Philippides A, Rojas N, 2020,

    A robust geometric method of singularity avoidance for kinematically redundant planar parallel robot manipulators

    , Mechanism and Machine Theory, Vol: 151, Pages: 103863-103863, ISSN: 0094-114X
  • Journal article
    He L, Lu Q, Abad S-A, Rojas N, Nanayakkara DPTet al., 2020,

    Soft fingertips with tactile sensing and active deformation for robust grasping of delicate objects

    , IEEE Robotics and Automation Letters, Vol: 5, Pages: 2714-2721, ISSN: 2377-3766

    Soft fingertips have shown significant adaptability for grasping a wide range of object shapes, thanks to elasticity. This ability can be enhanced to grasp soft, delicate objects by adding touch sensing. However, in these cases, the complete restraint and robustness of the grasps have proved to be challenging, as the exertion of additional forces on the fragile object can result in damage. This letter presents a novel soft fingertip design for delicate objects based on the concept of embedded air cavities, which allow the dual ability of tactile sensing and active shape-changing. The pressurized air cavities act as soft tactile sensors to control gripper position from internal pressure variation; and active fingertip deformation is achieved by applying positive pressure to these cavities, which then enable a delicate object to be kept securely in position, despite externally applied forces, by form closure. We demonstrate this improved grasping capability by comparing the displacement of grasped delicate objects exposed to high-speed motions. Results show that passive soft fingertips fail to restrain fragile objects at accelerations as low as 0.1 m/s 2 , in contrast, with the proposed fingertips delicate objects are completely secure even at accelerations of more than 5 m/s 2 .

  • Journal article
    Lu Q, Clark A, Shen M, Rojas Net al., 2020,

    An origami-inspired variable friction surface for increasing the dexterity of robotic grippers

    , IEEE Robotics and Automation Letters, Vol: 5, Pages: 2538-2545, ISSN: 2377-3766

    While the grasping capability of robotic grippers has shown significant development, the ability to manipulate objects within the hand is still limited. One explanation for this limitation is the lack of controlled contact variation between the grasped object and the gripper. For instance, human hands have the ability to firmly grip object surfaces, as well as slide over object faces, an aspect that aids the enhanced manipulation of objects within the hand without losing contact. In this letter, we present a parametric, origami-inspired thin surface capable of transitioning between a high friction and a low friction state, suitable for implementation as an epidermis in robotic fingers. A numerical analysis of the proposed surface based on its design parameters, force analysis, and performance in in-hand manipulation tasks is presented. Through the development of a simple two-fingered two-degree-of-freedom gripper utilizing the proposed variable-friction surfaces with different parameters, we experimentally demonstrate the improved manipulation capabilities of the hand when compared to the same gripper without changeable friction. Results show that the pattern density and valley gap are the main parameters that effect the in-hand manipulation performance. The origami-inspired thin surface with a higher pattern density generated a smaller valley gap and smaller height change, producing a more stable improvement of the manipulation capabilities of the hand.

  • Journal article
    Zhao M, Oude Vrielink TJC, Kogkas A, Runciman M, Elson D, Mylonas Get al., 2020,

    LaryngoTORS: a novel cable-driven parallel robotic system for transoral laser phonosurgery

    , IEEE Robotics and Automation Letters, Vol: 5, Pages: 1516-1523, ISSN: 2377-3766

    Transoral laser phonosurgery is a commonly used surgical procedure in which a laser beam is used to perform incision, ablation or photocoagulation of laryngeal tissues. Two techniques are commonly practiced: free beam and fiber delivery. For free beam delivery, a laser scanner is integrated into a surgical microscope to provide an accurate laser scanning pattern. This approach can only be used under direct line of sight, which may cause increased postoperative pain to the patient and injury, is uncomfortable for the surgeon during prolonged operations, the manipulability is poor and extensive training is required. In contrast, in the fiber delivery technique, a flexible fiber is used to transmit the laser beam and therefore does not require direct line of sight. However, this can only achieve manual level accuracy, repeatability and velocity, and does not allow for pattern scanning. Robotic systems have been developed to overcome the limitations of both techniques. However, these systems offer limited workspace and degrees-of-freedom (DoF), limiting their clinical applicability. This work presents the LaryngoTORS, a robotic system that aims at overcoming the limitations of the two techniques, by using a cable-driven parallel mechanism (CDPM) attached at the end of a curved laryngeal blade for controlling the end tip of the laser fiber. The system allows autonomous generation of scanning patterns or user driven freepath scanning. Path scan validation demonstrated errors as low as 0.054±0.028 mm and high repeatability of 0.027±0.020 mm (6×2 mm arc line). Ex vivo tests on chicken tissue have been carried out. The results show the ability of the system to overcome limitations of current methods with high accuracy and repeatability using the superior fiber delivery approach.

  • Journal article
    Liow L, Clark A, Rojas N, 2020,

    OLYMPIC: a modular, tendon-driven prosthetic hand with novel finger and wrist coupling mechanisms

    , IEEE Robotics and Automation Letters, Vol: 5, Pages: 299-306, ISSN: 2377-3766

    Prosthetic hands, while having shown significant progress in affordability, typically suffer from limited repairability, specifically by the user themselves. Several modular hands have been proposed to address this, but these solutions require handling of intricate components or are unsuitable for prosthetic use due to the large volume and weight resulting from added mechanical complexity to achieve this modularity. In this paper, we propose a fully modular design for a prosthetic hand with finger and wrist level modularity, allowing the removal and attachment of tendon-driven fingers without the need for tools, retendoning, and rewiring. Our innovative design enables placement of the motors behind the hand for remote actuation of the tendons, which are contained solely within the fingers. Details of the novel coupling-transmission mechanisms enabling this are presented; and the capabilities of a prototype using a control-independent grasping benchmark are discussed. The modular detachment torque of the fingers is also computed to analyse the trade-off between intentional removal and the ability to withstand external loads. Experiment results demonstrate that the prosthetic hand is able to grasp a wide range of household and food items, of different shape, size, and weight, without resulting in the ejection of fingers, while allowing a user to remove them easily using a single hand.

  • Journal article
    Russell F, Kormushev P, Vaidyanathan R, Ellison Pet al., 2020,

    The impact of ACL laxity on a bicondylar robotic knee and implications in human joint biomechanics

    , IEEE Transactions on Biomedical Engineering, ISSN: 0018-9294

    Objective: Elucidating the role of structural mechanisms in the knee can improve joint surgeries, rehabilitation, and understanding of biped locomotion. Identification of key features, however, is challenging due to limitations in simulation and in-vivo studies. In particular the coupling of the patello-femoral and tibio-femoral joints with ligaments and its impact on joint mechanics and movement is not understood. We investigate this coupling experimentally through the design and testing of a robotic sagittal plane model. Methods: We constructed a sagittal plane robot comprised of: 1) elastic links representing cruciate ligaments; 2) a bi-condylar joint; 3) a patella; and 4) actuator hamstrings and quadriceps. Stiffness and geometry were derived from anthropometric data. 10° - 110° squatting tests were executed at speeds of 0.1 - 0.25Hz over a range of anterior cruciate ligament (ACL) slack lengths. Results: Increasing ACL length compromised joint stability, yet did not impact quadriceps mechanical advantage and force required for squat. The trend was consistent through varying condyle contact point and ligament force changes. Conclusion: The geometry of the condyles allows the ratio of quadriceps to patella tendon force to compensate for contact point changes imparted by the removal of the ACL. Thus the system maintains a constant mechanical advantage. Significance: The investigation uncovers critical features of human knee biomechanics. Findings contribute to understanding of knee ligament damage, inform procedures for knee surgery and orthopaedic implant design, and support design of trans-femoral prosthetics and walking robots. Results further demonstrate the utility of robotics as a powerful means of studying human joint biomechanics.

  • Conference paper
    Pardo F, Levdik V, Kormushev P, 2020,

    Scaling all-goals updates in reinforcement learning using convolutional neural networks

    , 34th AAAI Conference on Artificial Intelligence (AAAI 2020), Publisher: Association for the Advancement of Artificial Intelligence, Pages: 5355-5362, ISSN: 2374-3468

    Being able to reach any desired location in the environmentcan be a valuable asset for an agent. Learning a policy to nav-igate between all pairs of states individually is often not fea-sible. Anall-goals updatingalgorithm uses each transitionto learn Q-values towards all goals simultaneously and off-policy. However the expensive numerous updates in parallellimited the approach to small tabular cases so far. To tacklethis problem we propose to use convolutional network archi-tectures to generate Q-values and updates for a large numberof goals at once. We demonstrate the accuracy and generaliza-tion qualities of the proposed method on randomly generatedmazes and Sokoban puzzles. In the case of on-screen goalcoordinates the resulting mapping from frames todistance-mapsdirectly informs the agent about which places are reach-able and in how many steps. As an example of applicationwe show that replacing the random actions inε-greedy ex-ploration by several actions towards feasible goals generatesbetter exploratory trajectories on Montezuma’s Revenge andSuper Mario All-Stars games.

  • Conference paper
    Saputra RP, Rakicevic N, Kormushev P, 2020,

    Sim-to-real learning for casualty detection from ground projected point cloud data

    , 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), Publisher: IEEE

    This paper addresses the problem of human body detection-particularly a human body lying on the ground (a.k.a. casualty)-using point cloud data. This ability to detect a casualty is one of the most important features of mobile rescue robots, in order for them to be able to operate autonomously. We propose a deep-learning-based casualty detection method using a deep convolutional neural network (CNN). This network is trained to be able to detect a casualty using a point-cloud data input. In the method we propose, the point cloud input is pre-processed to generate a depth image-like ground-projected heightmap. This heightmap is generated based on the projected distance of each point onto the detected ground plane within the point cloud data. The generated heightmap-in image form-is then used as an input for the CNN to detect a human body lying on the ground. To train the neural network, we propose a novel sim-to-real approach, in which the network model is trained using synthetic data obtained in simulation and then tested on real sensor data. To make the model transferable to real data implementations, during the training we adopt specific data augmentation strategies with the synthetic training data. The experimental results show that data augmentation introduced during the training process is essential for improving the performance of the trained model on real data. More specifically, the results demonstrate that the data augmentations on raw point-cloud data have contributed to a considerable improvement of the trained model performance.

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