This study aimed to examine different trajectory correction methods for spiral imaging on a preclinical scanner with high-performance gradients with respect to image quality in a phantom and in vivo. The gold standard method of measuring the trajectories in a separate experiment is compared to an isotropic delay-correction, a correction using the gradient system transfer function (GSTF), and a combination of the two. Three different spiral trajectories, with 96, 16, and three interleaves, are considered. The best image quality is consistently achieved when determining the trajectory in a separate phantom measurement. However, especially for the spiral with 96 interleaves, the other correction methods lead to almost comparable results. Remaining imperfections in the corrected gradient waveforms and trajectories are attributed to asymmetrically occurring undulations in the actual, generated gradients, suggesting that the underlying assumption of linearity is violated. In conclusion, images of sufficient quality can be acquired on preclinical small-animal scanners using spiral k-space trajectories without the need to carry out separate trajectory measurements each time. Depending on the trajectory, a simple isotropic delay-correction or a GSTF-based correction can provide images of similar quality.

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There is an established idea – found in science fiction, architectural studios, and scientific papers alike – of stainable buildings crafted from bio-based materials, colonized by plant and animal life, and blending seamlessly into the natural surroundings. Such buildings might one day be built, maintained and remodelled by swarms of autonomous robots, allowing them to evolve in response to the changing needs of their inhabitants. Inspired by that vision, this paper contributes to the field of swarm intelligence with a focus on robotic construction and human-swarm interaction. Along with a short literature review on robotic building, swarm intelligence and biocompatible building materials, the paper presents an open-source simulation of abstracted termite-like swarm construction. The focus is mainly on human-swarm interaction, specifically how to influence the emergent behaviour of an autonomous swarm in order to elicit a desired outcome while retaining the robustness and adaptability of a self-organized system. The simulator is used to demonstrate a set of four autonomous swarm behaviours that are representative of construction tasks.@en

Purpose: Tensor-valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the technical feasibility of tensor-valued diffusion encoding at high b-values with q-space trajectory imaging (QTI) analysis, in the human heart in vivo. Methods: Ten healthy volunteers were scanned on a 3T scanner. We designed time-optimal gradient waveforms for tensor-valued diffusion encoding (linear and planar) with second-order motion compensation. Data were analyzed with QTI. Normal values and repeatability were investigated for the mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (μFA), isotropic, anisotropic and total mean kurtosis (MKi, MKa, and MKt), and orientation coherence (C_c). A phantom, consisting of two fiber blocks at adjustable angles, was used to evaluate sensitivity of parameters to orientation dispersion and diffusion time. Results: QTI data in the left ventricular myocardium were MD = 1.62 ± 0.07 μm²/ms, FA = 0.31 ± 0.03, μFA = 0.43 ± 0.07, MKa = 0.20 ± 0.07, MKi = 0.13 ± 0.03, MKt = 0.33 ± 0.09, and C_c = 0.56 ± 0.22 (mean ± SD across subjects). Phantom experiments showed that FA depends on orientation dispersion, whereas μFA was insensitive to this effect. Conclusion: We demonstrated the first tensor-valued diffusion encoding and QTI analysis in the heart in vivo, along with first measurements of myocardial μFA, MKi, MKa, and C_c. The methodology is technically feasible and provides promising novel biomarkers for myocardial tissue characterization.

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Swarm foraging is a common test case application for multi-robot systems. In this paper RepAtt algorithm is used for improving coordination of a robot swarm by selectively broadcasting repulsion and attraction signals. This is a chemotaxis-inspired search behaviour where robots use the temporal gradients of these signals to navigate towards more advantageous areas. Hardware experiments were used to model and validate realistic, noisy sound communication and vision system. We then show through extensive simulation studies that RepAtt significantly improves swarm foraging time and robot efficiency under realistic communication and vision models. Note to Practitioners - This research developed a swarm foraging algorithm that takes into consideration the vision and communication sensing noise levels faced by robots in real world applications. The algorithm, known as RepAtt, was developed with the aim of emphasizing algorithmic simplicity and limiting the hardware requirements for the robots in the swarm. In this paper, we have focused on the problem of deploying swarm robots to forage litter in an environment such as a park. The communication model of the robots was based on the physics of sound, while their vision system was modelled using experiments with deep neural networks based object detectors. The results show that the RepAtt algorithm is robust to different distributions of targets (or litter) in the search space, exhibits good swarm efficiency with changes in swarm population and is robust to noise in its communication and vision systems. Apart from the RepAtt algorithm, other contributions made by this research include modelling of robot vision system to aid extensive study of the impact of communication and vision noise on swarm coordination. This will be relevant for extensive testing and validation before deployment to swarm robots hardware. The sound communication used in this research limits the kinds of environment the robots can be deployed in. Echoes within an enclosed environment and bandwidth limitation for communication frequency and public disturbance due to sound emitted by the robots can all contribute to this limitation. Thus, this research can be improved by investing in the development of a communication technology with similar physics. Other areas of improvement include adopting better obstacle avoidance algorithms and implementing suitable manipulators for handling litter objects. The algorithm can be extended to make it applicable for solving other problems such as search and rescue operations where foraging targets could be disaster survivors; demining and hazardous waste cleanup, where targets are the mines or waste material; and planetary exploration, where targets could be interesting features of the planets are the targets searched for by the robots.

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Small inspection robots allow for the optimal exploration of environments and the collection of data from challenging areas, particularly where there may be small access points or tight and fragile surroundings. These robots can be custom-built for specific tasks, but the design and assembly process for this can be costly, both in resources and assembly time. The use of 3D printing to create Non-Assembly mechanisms can assist in saving time and resources by reducing the number of different components required and removing the necessity for complex assembly tasks. By iterating on previous work performed in the institute, this paper introduces a novel robot design to push the capabilities of Non-Assembly systems. By building on previous knowledge, this new walking robot improves on the previous iteration by creating a more robust and reliable system, more capable of effectively exploring challenging environments accurately, while still using practices designed to save on cost and production time. Benchmark tests were performed to provide an accurate comparison against the previous design and highlight the robots marked improvements in positional accuracy over its predecessor@en

Despite recent advances in robotic technology, sewer pipe inspection is still limited to conventional approaches that use cable-tethered robots. Such commercially available tethered robots lack autonomy, and their operation must be manually controlled via their tethered cables. Consequently, they can only travel to a certain distance in pipe, cannot access small-diameter pipes, and their deployment incurs high costs for highly skilled operators. In this paper, we introduce a miniaturised mobile robot for pipe inspection. We present an autonomous control strategy for this robot that is effective, stable, and requires only low-computational resources. The robots used here can access pipes as small as 75 mm in diameter. Due to their small size, low carrying capacity, and limited battery supply, our robots can only carry simple sensors, a small processor, and miniature wheel-legs for locomotion. Yet, our control method is able to compensate for these limitations. We demonstrate fully autonomous robot mobility in a sewer pipe network, without any visual aid or power-hungry image processing. The control algorithm allows the robot to correctly recognise each local network configuration, and to make appropriate decisions accordingly. The control strategy was tested using the physical micro robot in a laboratory pipe network. In both simulation and experiment, the robot autonomously and exhaustively explored an unknown pipe network without missing any pipe section while avoiding obstacles. This is a significant advance towards fully autonomous inspection robot systems for sewer pipe networks.

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The manufacture and assembly of small-scale robotics can be expensive and time-consuming using traditional methods; especially when complex mechanisms are involved. By refining current additive manufacturing techniques a micro-scale walking robot can be 3D printed without the need for any complex mechanical assembly. The robot requires only the addition of simple circuitry and 2 motors, one for each of the 1 degree of freedom walking mechanisms before it is capable of being driven wirelessly. Once fully assembled, differential drive of the parallel leg sets allows for locomotion in any direction on a 2-D plane. The robot’s compact size; just 62 mm (x) × 38 mm (y) × 88 mm (z), and leg curvature makes travel possible through borehole/pipe diameters as low as 65 mm. By pushing printer tolerances to the limit, complex mechanisms can work in Non-Assembly at a small scale. Through the Query application of these Non-Assembly techniques to field robots such as those intended for use in the Pipebots project could allow for the production of large swarms of robots quickly and affordably.

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Changes in composition of the intestinal microbiota are linked to the development of obesity and can lead to endothelial cell (EC) dysfunction. It is unknown whether EC can directly influence the microbiota. Insulin-like growth factor-1 (IGF-1) and its receptor (IGF-1R) are critical for coupling nutritional status and cellular growth; IGF-1R is expressed in multiple cell types including EC. The role of ECIGF-1R in the response to nutritional obesity is unexplored. To examine this, we use gene-modified mice with EC-specific overexpression of human IGF-1R (hIGFREO) and their wild-type littermates. After high-fat feeding, hIGFREO weigh less, have reduced adiposity and have improved glucose tolerance. hIGFREO show an altered gene expression and altered microbial diversity in the gut, including a relative increase in the beneficial genus Akkermansia. The depletion of gut microbiota with broad-spectrum antibiotics induces a loss of the favourable metabolic differences seen in hIGFREO mice. We show that IGF-1R facilitates crosstalk between the EC and the gut wall; this crosstalk protects against diet-induced obesity, as a result of an altered gut microbiota.

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Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%–20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites) sequence, and a custom motion-compensated spin echo (SE; N = 5) or stimulated echo acquisition mode (STEAM; N = 5) sequence suitable for cardiac DTI in vivo. A second identical scan was performed 1–9 days later, and the data were analysed centrally. The average mean diffusivities (MDs) in 0% PVP were (1.124, 1.130, 1.113) x 10⁻³ mm²/s for PGSE, SE and STEAM, respectively, and accurate to within 1.5% of reference data from the literature. The coefficients of variation in MDs across sites were 2.6%, 3.1% and 2.1% for PGSE, SE and STEAM, respectively, and were similar to previous studies using only PGSE. Reproducibility in MD was excellent, with mean differences in PGSE, SE and STEAM of (0.3 ± 2.3, 0.24 ± 0.95, 0.52 ± 0.58) x 10⁻⁵ mm²/s (mean ± 1.96 SD). We show that custom sequences for cardiac DTI provide accurate, precise, repeatable and reproducible measurements. Further work in anisotropic and/or deforming phantoms is warranted.

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Swarm foraging is a common test case application for multi-robot systems. In this paper we present a novel algorithm for improving coordination of a robot swarm by selectively broadcasting repulsion and attraction signals. Robots use a chemotaxis-inspired search behaviour based on the temporal gradients of these signals in order to navigate towards more advantageous areas. Hardware experiments were used to model and validate realistic, noisy sound communication. We then show through extensive simulation studies that our chemotaxis-based coordination algorithm significantly improves swarm foraging time and robot efficiency.

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Purpose: This paper aims to present a multi-axis additive robot manufacturing system (ARMS) and demonstrate its beneficial capabilities. Design/methodology/approach: ARMS was constructed around two robot arms and a fused filament fabrication (FFF) extruder. Quantitative experiments are conducted to investigate the effect of printing at different orientations with respect to gravity, the effect of dynamically changing build orientation with respect to the build tray when printing overhanging features, the effect of printing curved parts using curved, conformal layers. These capabilities are combined to print an integrated demonstrator showing potential practical benefits of the system. Findings: Orientation with respect to gravity has no effect on print quality; dynamically changing build orientation allows overhangs up to 90° to be cleanly printed without support structures; printing an arch with conformal layers significantly increases its strength compared to conventional printing. Research limitations/implications: The challenge of automatic slicing algorithms has not been addressed for multi-axis printing. It is shown that ARMS could eventually enable printing of fully-functional prototypes with embedded components. Originality/value: This work is the first to prove that the surface roughness of an FFF part is independent of print orientation with respect to gravity. The use of two arms creates a novel system with more degrees of freedom than existing multi-axis printers, enabling studies on printing orientation relationships and printing around inserts. It also adds to the emerging body of multi-axis literature by verifying that curved layers improve the strength of an arch which is steeply curved and printed with the nozzle remaining normal to the curvature.

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Goal: Tread patterns are widely used to increase traction on different substrates, with the tread scale, geometry and material being tailored to the application. This work explores the efficacy of using macro-scale tread patterns for a medical application involving a colon substrate - renowned for its low friction characteristics. Methods: Current literature was first summarized before an experimental approach was used, based on a custom test rig with ex vivo porcine colon, to assess different macro-scale tread patterns. Performance was based on increasing traction while avoiding significant trauma. Repeated testing (n = 16) was used to obtain robust results. Results: A macro-scale tread pattern can increase the traction coefficient significantly, with a static traction coefficient of 0.74 ± 0.22 and a dynamic traction coefficient of 0.35 ± 0.04 compared to a smooth (on the macro-scale) Control (0.132 ± 0.055 and 0.054 ± 0.015, respectively). Decreasing the scale and spacing between the tread features reduced apparent trauma but also reduced the traction coefficient. Conclusion: Significant traction can be achieved on colon tissue using a macro-scale tread but a compromise between traction (large feature sizes) and trauma (small feature sizes) may have to be made. Significance: This work provides greater insight into the complex frictional mechanisms of the intestine and gives suggestions for developing functional tread surfaces for a wide range of clinical applications.

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This work details the design and simulation results of a bioinspired minimalist algorithm based on C. elegans, using autonomous agents to forage for attractant energy sources. The robotic agents are energy-constrained and depend on the energy they forage to recharge their batteries, which is significant as the foraging task is one of the canonical testbeds for cooperative robotics. The algorithm consists of 6 input parameters which were simulated and optimised in 9 unbounded environments of varying difficulty levels, containing attractant sources which robots would then have to forage from to maintain energy levels and survive the entirety of the simulation. The robots running the algorithm were then optimised using Evolutionary Algorithms and the best solutions in all 9 environments were categorised with the use of clustering techniques. The clustering results highlighted the different strategies which emerged. Ultimately across the 9 environments, 6 different strategies have been identified. The results demonstrate the applicability of the proposed algorithm to localise attractant sources and harvest energy in different scenarios using the same core algorithm.

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This paper presents the development of a tendon-driven continuum robot segment with a modular design, simple construction and significant lifting capabilities. The segment features a continuous flexible core combined with rigid interlocking vertebrae evenly distributed along its length. This design allows bending in two degrees of freedom while minimising torsional movement. The segment is actuated by two antagonistic tendon pairs, each of which is driven by a single geared DC motor. Modularity is achieved by embedding these motors in one end of the segment, avoiding the need for a bulky actuation unit and allowing variable numbers of segments to be connected. The design features a large hollow central bore which could be used as a vacuum channel for suction-assisted gripping or to allow ingress and egress of fluids. The design process goes through four iterations, the final two of which are subjected to quantitative experiments to evaluate workspace, lifting capabilities and torsional rigidity. All iterations are fabricated using multi-material 3D printing, which allows the entire structure to be printed as a pre-assembled unit with the rigid vertebrae fused to the flexible core. Assembly is then a simple case of inserting the motors and connecting the tendons. This unconventional manufacturing approach is found to be efficient, effective and relatively cheap.

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This paper presents a novel swarm robotics application of chemotaxis behaviour observed in microorganisms. This approach was used to cause exploration robots to return to a work area around the swarm’s nest within a boundless environment. We investigate the performance of our algorithm through extensive simulation studies and hardware validation. Results show that the chemotaxis approach is effective for keeping the swarm close to both stationary and moving nests. Performance comparison of these results with the unrealistic case where a boundary wall was used to keep the swarm within a target search area showed that our chemotaxis approach produced competitive results.

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There are currently a number of major drawbacks to using a colonoscope that limit its efficacy. One solution to this may be to use a warm liquid to distend the colon during inspection. Another is to replace the colonoscope with a small mobile robot-a solution many believe is the future of gastrointestinal intervention. This paper presents RollerBall, an intraluminal robot that uses wheeled-locomotion to traverse the length of a fluid-filled colon. The device provides a central, stable platform within the lumen for the use of diagnostic and therapeutic tools. The concept is described in detail and the feasibility demonstrated in a series of tests in a synthetic colon.

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Compliant actuation methods are popular in robotics applications where interaction with complex and unpredictable environments and objects is required. There are a number of ways of achieving this, but one common method is Series Elastic Actuation (SEA). In a recent version of their Unified Snake robot, Choset et al. incorporated a Series Elastic Element (SEE) in the form of a rubber torsional spring. This paper explores the possibility of using multi-material 3D printing to produce similar SEEs. This approach would facilitate the fabrication and testing of different springs and minimize the assembly required. This approach is evaluated by characterizing the behavior of two configurations of SEE, 3d printed with different dimensions. The springs exhibit predictable viscoelastic behavior that is well described by a five element Wiechert model. We find that individual springs behave predictably and that multiple copies of the same spring design exhibit good consistency.

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Although significant progress has been made in the development of robots with serpentine properties, the issues of motion control and adaptation to environmental constraints still require substantial research. This is particularly true for search and rescue applications, where reliable operation in extremely difficult terrain is essential. This paper presents a novel robot design based on the mechanics and neural control of locomotion in Caenorhabditis elegans, a tiny nematode worm. Equipped with an extremely simple yet powerful neurally-inspired decentralized control system, the robot presented here is capable of effective serpentine locomotion. More importantly, it exhibits sensorless path finding, in which obstacles in the environment are overcome, based purely on proprioceptive feedback encoding body shape. Indeed, the robot lacks any form of external sensory capability. The design and implementation of the prototype robot and its control strategy are discussed. In order to validate the control strategy for path finding, experiments and analyses have been performed. The results show that the robot can find its path successfully in the majority of cases. The current limitations have also been discussed. © 2012 IEEE.@en

Equipped with its 302-cell nervous system, the nematode Caenorhabditis elegans adapts its locomotion in different environments, exhibiting so-called swimming in liquids and crawling on dense gels. Recent experiments have demonstrated that the worm displays the full range of intermediate behaviors when placed in intermediate environments. The continuous nature of this transition strongly suggests that these behaviors all stem from modulation of a single underlying mechanism. We present a model of C. elegans forward locomotion that includes a neuromuscular control system that relies on a sensory feedback mechanism to generate undulations and is integrated with a physical model of the body and environment. We find that the model reproduces the entire swim-crawl transition, as well as locomotion in complex and heterogeneous environments. This is achieved with no modulatory mechanism, except via the proprioceptive response to the physical environment. Manipulations of the model are used to dissect the proposed pattern generation mechanism and its modulation. The model suggests a possible role for GABAergic D-class neurons in forward locomotion and makes a number of experimental predictions, in particular with respect to nonlinearities in the model and to symmetry breaking between the neuromuscular systems on the ventral and dorsal sides of the body. © 2012 Boyle, Berri and Cohen.@en