This paper introduces a pose sensing system for soft robot arms integrating a set of macrobend stretch sensors. The macrobend sensory design in this study consists of optical fibres and is based on the notion that bending an optical fibre modulates the intensity of the light transmitted through the fibre.This sensing method is capable of measuring bending, elongation and compression in soft continuum robots and is also applicable to wearable sensing technologies, e.g. pose sensing in the wrist joint of a human hand. In our arrangement, applied to a cylindrical soft robot arm, the optical fibres for macrobend sensing originate from the base, extend to the tip of the arm, and then loop back to the base. The connectors that link the fibres to the necessary opto-electronics are all placed at the base of the arm, resulting in a simplified overall design.The ability of this custom macrobend stretch sensor to flexibly adapt its configuration allows preserving the inherent softness and compliance of the robot which it is installed on. The macrobend sensing system is immune to electrical noise and magnetic fields, is safe (because no electricity is needed at the sensing site), and is suitable for modular implementation in multi-link soft continuum robotic arms.The measurable light outputs of the proposed stretch sensor vary due to bend-induced light attenuation (macrobend loss), which is a function of the fibre bend radius as well as the number of repeated turns. The experimental study conducted as part of this research revealed that the chosen bend radius has a far greater impact on the measured light intensity values than the number of turns (if greater than five). Taking into account that the bend radius is the only significantly influencing design parameter, the macrobend stretch sensors were developed to create a practical solution to the pose sensing in soft continuum robot arms. Henceforward, the proposed sensing design was benchmarked against an electromagnetic tracking system (NDI Aurora) for validation.

Cilia are used effectively in a wide variety of biological systems from fluid transport to thrust generation. Here, we present the design and implementation of artificial cilia, based on a biomimetic planar actuator using softsmart materials. This actuator is modelled on the cilia movement of the alga Volvox, and represents the cilium as a piecewise constant-curvature robotic actuator that enables the subsequent direct translation of natural articulation into a multi-segment ionic polymer metal composite actuator. It is demonstrated how the combination of optimal segmentation pattern and biologically derived per-segment driving signals reproduce natural ciliary motion. The amenability of the artificial cilia to scaling is also demonstrated through the comparison of the Reynolds number achieved with that of natural cilia.

This paper presents a robotic anchoring module, a sensorised mechanism for attachment to the environment that can be integrated into robots to enable or enhance various functions such as robot mobility, remaining on location or its ability to manipulate objects. The body of the anchoring module consists of two portions with a mechanical stiffness transition from hard to soft. The hard portion is capable of containing vacuum pressure used for actuation whilst the soft portion is highly conformable to create a seal to contact surfaces. The module is integrated with a single sensory unit which exploits a fibre optic sensing principle to seamlessly measure proximity and tactile information for use in robot motion planning as well as measuring the state of firmness of its anchor. In an experiment, a variable set of physical loads representing the weights of potential robot bodies were attached to the module and its ability to maintain the anchor was quantified under constant and variable vacuum pressure signals. The experiment shows the effectiveness of the module in quantifying the state of firmness of the anchor and discriminating between different amounts of physical loads attached to it. The proposed anchoring module can enable many industrial and medical applications where attachment to environment is of crucial importance for robot control.

Robotic manipulators for Robot-assisted Minimally Invasive Surgery (RMIS) pass through small incisions into the patient's body and interact with soft internal organs. The performance of traditional robotic manipulators such as the da Vinci Robotic System is limited due to insufficient flexibility of the manipulator and lack of haptic feedback. Modern surgical manipulators have taken inspiration from biology e.g. snakes or the octopus. In order for such soft and flexible arms to reconfigure itself and to control its pose with respect to organs as well as to provide haptic feedback to the surgeon, tactile sensors can be integrated with the robot's flexible structure. The work presented here takes inspiration from another area of biology: cucumber tendrils have shown to be ideal tactile sensors for the plant that they are associated with providing useful environmental information during the plant's growth. Incorporating the sensing principles of cucumber tendrils, we have created miniature sensing elements that can be distributed across the surface of soft manipulators to form a sensor network capable of acquire tactile information. Each sensing element is a retractable hemispherical tactile measuring applied pressure. The actual sensing principle chosen for each tactile makes use of optic fibres that transfer light signals modulated by the applied pressure from the sensing element to the proximal end of the robot arm. In this paper, we describe the design and structure of the sensor system, the results of an analysis using Finite Element Modeling in ABAQUS as well as sensor calibration and experimental results. Due to the simple structure of the proposed tactile sensor element, it is miniaturisable and suitable for MIS. An important contribution of this work is that the developed sensor system can be "loosely" integrated with a soft arm effectively operating independently of the arm and without affecting the arm's motion during bending or elongation.

Abstract:In this paper we present bio-inspired smart structures which exploit the actuation of flexible ionic polymer composites and the kirigami design principle. Kirigami design is used to convert planar actuators into active 3D structures capable of large out-of-plane displacement and that replicate biological mechanisms. Here we present the burstbot, a fluid control and propulsion mechanism based on the atrioventricular cuspid valve, and the vortibot, a spiral actuator based on Vorticella campanula, a ciliate protozoa. Models derived from biological counterparts are used as a platform for design optimisation and actuator performance measurement. The symmetric and asymmetric fluid interactions of the burstbot are investigated and the effectiveness in fluid transport applications is demonstrated. The vortibot actuator is geometrically optimised as a camera positioner capable of 360 degree scanning. Experimental results for a one-turn spiral actuator show complex actuation derived from a single degree of freedom control signal.

Flexible soft and stiffness-controllable surgical manipulators enhance the manoeuvrability of surgical tools during Minimally Invasive Surgery (MIS), as opposed to conventional rigid laparoscopic instruments. These flexible and soft robotic systems allow bending around organs, navigating through complex anatomical pathways inside the human body and interacting inherently safe with its soft environment. Shape sensing in such systems is a challenge and one essential requirement for precise position feedback control of soft robots. This paper builds on our previous work integrating multiple optical fibres into a soft manipulator to estimate the robot's pose using light intensity modulation. Here, we present an enhanced version of our embedded bending/shape sensor based on electro-conductive yarn. The new system is miniaturised and able to measure bending behaviour as well as elongation. The integrated yarn material is helically wrapped around an elastic strap and protected inside a 1.5mm outer-diameter stretchable pipe. Three of these resulting stretch sensors are integrated in the periphery of a pneumatically actuated soft manipulator for direct measurement of the actuation chamber lengths. The capability of the sensing system in measuring the bending curvature and elongation of the arm is evaluated.

This paper describes a multi-fingered haptic palpation method using stiffness feedback actuators for simulating tissue palpation procedures in traditional and robot-assisted minimally invasive surgery. Soft tissue stiffness is simulated by changing the stiffness property of the actuator during palpation. For the first time, granular jamming and pneumatic air actuation are combined together to realize stiffness modulation. The stiffness feedback actuator is validated by stiffness measurements in indentation tests and through stiffness discrimination based on a user study. According to the indentation test results, the introduction of a pneumatic chamber to granular jamming can amplify the stiffness variation range and reduce hysteresis of the actuator. The advantage of multi-fingered palpation using the proposed actuators is proven by the comparison of the results of the stiffness discrimination performance using two-fingered (sensitivity: 82.2%, specificity: 88.9%, positive predicative value: 80.0%, accuracy: 85.4%, time: 4.84 s) and single-fingered (sensitivity: 76.4%, specificity: 85.7%, positive predicative value: 75.3%, accuracy: 81.8%, time: 7.48 s) stiffness feedback.

Additive manufacturing methods 1-4 using static and mobile robots are being developed for both on-site construction 5-8 and off-site prefabrication 9, 10 . Here we introduce a new method of additive manufacturing, referred to as Aerial Additive Manufacturing (Aerial-AM), that utilizes a team of aerial robots inspired by natural builders 11 such as wasps who use collective building methods 12, 13 . We present a scalable multi-robot 3D printing and path planning framework that enables robot tasks and population size to be adapted to variations in print geometry throughout a building mission. The multi-robot manufacturing framework allows for autonomous 3D printing under human supervision, real-time assessment of printed geometry and robot behavioural adaptation. To validate autonomous Aerial-AM based on the framework, we develop BuilDrones for depositing materials during flight and ScanDrones for measuring print quality, and integrate a generic real-time model-predictive-control scheme with the Aerial-AM robots. In addition, we integrate a dynamically self-aligning delta manipulator with the BuilDrone to further improve manufacturing accuracy to 5mm for printing geometry with precise trajectory requirements, and develop four cementitious-polymeric composite mixtures suitable for continuous material deposition. We demonstrate proof-of-concept prints including a cylinder of 2.05m with a rapid curing insulation foam material and a cylinder of 0.18m with structural pseudoplastic cementitious material, a light-trail virtual print of a dome-like geometry, and multi-robot simulations.