Search results

The purpose of this paper is to estimate the deformation of soft manipulators caused by obstacles accurately and the contact force and workspace can be also predicted.

The continuum deformation of the backbone of the soft manipulator under contact is regarded as two constant curvature arcs and the curvatures are different according to the fluid pressure and obstacle location based on piecewise constant curvature framework. Then, this study introduces introduce the moment balance and energy conservation equation to describe the static relationship between driving moment, elastic moment and contact moment. Finally, simulation and experiments are carried out to verify the accuracy of the proposed model.

For rigid manipulators, environmental contact except for the manipulated object was usually considered as a “collision” which should be avoided. For soft manipulators, an environment is an important tool for achieving manipulation goals and it might even be considered to be a part of the soft manipulator’s end-effector in some specified situations.

There are also some limitations to the presented study. Although this paper has made progress in the static modeling under environmental contact, some practical factors still limit the further application of the model, such as the detection accuracy of the environment location and the deformation of the contact surface.

Based on the proposed kinematic model, the bending deformation with environmental contact is discussed in simulations and has been experimentally verified. The comparison results show the correctness and accuracy of the presented SCC model, which can be applied to predict the slender deformation under environmental contact without knowing the contact force.

This paper aims to describe a recently proposed algorithm in terrain‐based cooperative UAV mapping of the unknown complex obstacle in a stationary environment where the complex obstacles are represented as curved in nature. It also aims to use an extended Kalman filter (EKF) to estimate the fused position of the UAVs and to apply the 2‐D splinegon technique to build the map of the complex shaped obstacles. The path of the UAVs are dictated by the Dubins path planning algorithm. The focus is to achieve a guaranteed performance of sensor based mapping of the uncertain environments using multiple UAVs.

An extended Kalman filter is used to estimate the position of the UAVs, and the 2‐D splinegon technique is used to build the map of the complex obstacle where the path of the UAVs are dictated by the Dubins path planning algorithm.

The guaranteed performance is quantified by explicit bounds of the position estimate of the multiple UAVs for mapping of the complex obstacles using 2‐D splinegon technique. This is a newly proposed algorithm, the most efficient and a robust way in terrain based mapping of the complex obstacles. The proposed method can provide mathematically provable and performance guarantees that are achievable in practice.

The paper describes the main contribution in mapping the complex shaped curvilinear objects using the 2‐D splinegon technique. This is a new approach where the fused EKF estimated positions are used with the limited number of sensors' measurements in building the map of the complex obstacles.

The purpose of this paper is to design a soft robot for performing detection, by using a hybrid drive to reach the target point faster and enable the robot to perform the detection task at a relatively fast speed.

The soft robot is driven by a mixture of motors and pneumatic pressure, in which the pneumatic pressure is used to drive the soft actuator to bend and the motors to drive the soft robot forward. The careful design of the actuator is based on a finite element simulation using ABAQUS, which combines a constant curvature differential model and the D-H method to analyze the motion space of the soft actuator.

The soft robot’s ability to adapt to the environment and cross obstacles has been demonstrated by building prototypes and complex environments such as grass, gravel, sand and pipes.

This design can improve the speed and smoothness of the motion of the soft robot, while retaining the good environmental flexibility of the soft robot. And the soft robot has good environmental adaptability and the ability to cross obstacles. The soft robot proposed in this paper has broad prospects in fields such as pipeline inspection and field exploration.

The structural adaptive ability of the soft robot is fully demonstrated in the grasping task of the soft hand. A soft hand can easily realize the envelope operation of the object without planning. With the continuous development of robot applications, researchers are no longer satisfied with the ability of the soft hand to grasp. The purpose of this paper is to perceive the object’s shape while grasping to provide a decision-making basis for more intelligent robot applications.

This paper proposes a dual-signal comparison method to obtain the fingertip position. The dual signal includes the displacement calculated by the static model without considering the external load change and the displacement calculated by the bending sensor. The dual-signal comparison method can use the obvious change trend difference between the above two signals in the hover and contact states to identify the touch position. The authors make the soft hand scan around the object through touch operation to detect the object’s shape, and the tracks of every touch fingertip position can envelop the object’s shape.

The experimental results show that the dual-signal comparison method can accurately identify the contact moment of soft fingers. This detection method makes the soft hand develop the shape detection ability. The soft hand in the experiment can perceive squares, circles and a few other complex shapes.

The dual-signal comparison method proposed in this paper can detect a touch action by using the signal change trend when the working condition suddenly changes with the rough robotic model and sensing, thus improving the utilization value of the measured signal. The problems of large model errors and inaccurate sensors also negatively impact the use of other soft robots. It is generally difficult to achieve good results by directly using these models and sensors with the thinking of rigid robot analysis. The dual-signal comparison method in this paper can provide some reference for this aspect.

In large equipment and highly complex confined workspaces, the maintenance is usually carried out by snake-arm robots with equal cross-sections. However, the equal cross-sectional design results in the snake arm suffering from stress concentration and restricted working space. The purpose of this paper is to design a variable cross-section elephant trunk robot (ETR) that can address these shortcomings through bionic principles.

This paper proposes a cable-driven ETR to explore the advantages and inspiration of variable cross-section features for hyper-redundant robot design. For the kinematic characteristics, the influence of the variable cross-section design on the maximum joint angle of the ETR is analysed using the control variables method and the structural parameters are selected. Based on the biological inspiration of the whole elephant trunk following the movement of the trunk tip, a trajectory-tracking algorithm is designed to solve the inverse kinematics of the ETR.

Simulation and test results show the unique advantages of the proposed variable cross-section ETR in kinematics and forces, which can reduce stress concentrations and increase the flexibility of movement.

This paper presents a design method for a variable cross-section ETR for confined working spaces, analyses the kinematic characteristics and develops a targeted trajectory control algorithm.

When establishing a mathematical model to simulate solid mechanics, considering realistic geometries, special tools are needed to translate measured data, possibly with noise, into idealized geometrical entities. As an engineering application, wheel-rail contact interactions are fundamental in the dynamic modeling of railway vehicles. Many approaches used to solve the contact problem require a continuous parametric description of the geometries involved. However, measured wheel and rail profiles are often available as sets of discrete points. A reconstruction method is needed to transform discrete data into a continuous geometry.

The authors present an approximation method based on optimization to solve the problem of fitting a set of points with an arc spline. It consists of an initial guess based on a curvature function estimated from the data, followed by a least-squares optimization to improve the approximation. The authors also present a segmentation scheme that allows the method to increment the number of segments of the spline, trying to keep it at a minimal value, to satisfy a given error tolerance.

The paper provides a better understanding of arc splines and how they can be deformed. Examples with parametric curves and slightly noisy data from realistic wheel and rail profiles show that the approach is successful.

The developed methods have theoretical value. Furthermore, they have practical value since the approximation approach is better suited to deal with the reconstruction of wheel/rail profiles than interpolation, which most methods use to some degree.

Rigid robotic hands are generally fast, precise and capable of exerting large forces, whereas soft robotic hands are compliant, safe and adaptive to complex environments. It is valuable and challenging to develop soft-rigid robotic hands that have both types of capabilities. The paper aims to address the challenge through developing a paradigm to achieve the behaviors of soft and rigid robotic hands adaptively.

The design principle of a two-joint finger is proposed. A kinematic model and a stiffness enhancement method are proposed and discussed. The manufacturing process for the soft-rigid finger is presented. Experiments are carried out to validate the accuracy of the kinematic model and evaluate the performance of the flexible body of the finger. Finally, a robotic hand composed of two soft-rigid fingers is fabricated to demonstrate its grasping capacities.

The kinematic model can capture the desired distal deflection and comprehensive shape accurately. The stiffness enhancement method guarantees stable grasp of the robotic hand, without sacrificing its flexibility and adaptability. The robotic hand is lightweight and practical. It can exhibit different grasping capacities.

It can be applied in the field of industrial grasping, where the objects are varied in materials and geometry. The hand’s inherent characteristic removes the need to detect and react to slight variations in surface geometry and makes the control strategies simple.

This work proposes a novel robotic hand. It possesses three distinct characteristics, i.e. high compliance, exhibiting discrete or continuous kinematics adaptively, lightweight and practical structures.

The purpose of this paper is to employ analytical and numerical techniques to generate modal displacement data of damaged beams containing very small crack-like surface flaws or slots and to use the data in the development of damage detection methodology. The detection method involves the use of double differentiation of the modal data for identification of the flaw location and magnitude.

The modal displacements of damaged beams are simulated analytically using the Bernoulli-Euler theory and numerically using the finite element method. The principle used in the analytical approach is based on changes in the transverse displacement due to the localized reduction of the flexural rigidity of the beam. Curvature analysis is employed to identify and locate the structural flaws from the modal data. The curvature mode shapes are calculated using a central difference approximation. The effects of random noise on the detectability of the structural flaws are also computed.

The analytical approach is much more robust in simulating modal displacement data for beams with crack-like surface flaws or slots than the finite element analysis (FEA) approach especially for crack-like surface flaws or slots of very small depths. The structural flaws are detectable in the presence of random noise of up to 5 per cent.

Simulating the effects of small crack-like surface flaws is important because it is essential to develop techniques to detect cracks at an early stage of their development. The FEA approach can only simulate the effects of crack-like surface flaws or slots with depth ratio greater than 10 per cent. On the other hand, the analytical approach using the Bernoulli-Euler theory can simulate the effects of crack-like surface flaws or slots with depth ratio as small as 2 per cent.

The performance of three frequently used level set-based segmentation methods is examined for the purpose of defining features and boundary conditions for image-based Eulerian fluid and solid mechanics models. The focus of the evaluation is to identify an approach that produces the best geometric representation from a computational fluid/solid modeling point of view. In particular, extraction of geometries from a wide variety of imaging modalities and noise intensities, to supply to an immersed boundary approach, is targeted.

Two- and three-dimensional images, acquired from optical, X-ray CT, and ultrasound imaging modalities, are segmented with active contours, k-means, and adaptive clustering methods. Segmentation contours are converted to level sets and smoothed as necessary for use in fluid/solid simulations. Results produced by the three approaches are compared visually and with contrast ratio, signal-to-noise ratio, and contrast-to-noise ratio measures.

While the active contours method possesses built-in smoothing and regularization and produces continuous contours, the clustering methods (k-means and adaptive clustering) produce discrete (pixelated) contours that require smoothing using speckle-reducing anisotropic diffusion (SRAD). Thus, for images with high contrast and low to moderate noise, active contours are generally preferable. However, adaptive clustering is found to be far superior to the other two methods for images possessing high levels of noise and global intensity variations, due to its more sophisticated use of local pixel/voxel intensity statistics.

It is often difficult to know a priori which segmentation will perform best for a given image type, particularly when geometric modeling is the ultimate goal. This work offers insight to the algorithm selection process, as well as outlining a practical framework for generating useful geometric surfaces in an Eulerian setting.

The purpose of this paper is to study the effect of curvature on the magnetic field distribution and no-load rotor eddy current losses in electric machines, particularly in high-speed permanent magnet (PM) machines.

The magnetic field distribution is obtained using conformal mapping, and the eddy current losses are obtained using a cylindrical multilayer model. The analytical results are validated using a two-dimensional finite element analysis. The analytical method is based on a proportional-logarithmic conformal transformation that maps the cylindrical geometry of a rotating electric machine into a rectangular configuration without modifying the length scale. In addition, the appropriate transformation of PM cylindrical domains into the rectangular domain is deduced. Based on this conformal transformation, a coefficient to quantify the effect of curvature is proposed.

Neglecting the effect of curvature can produce significant errors in the calculation of no-load rotor losses when the ratio between the air-gap length and the rotor diameter is large.

The appropriate transformation of PM cylindrical domains into the rectangular domain is deduced. The proportional-logarithmic transformation proposed provides an insight into the effect of curvature on the magnetic field distribution in the air-gap and no-load rotor losses. Furthermore, the proposed curvature coefficient gives a notion of the effect of curvature for any particular geometry without the necessity of any complicated calculation. The case study shows that neglecting the effect of curvature underestimates the rotor eddy-current losses significantly in machines with large gap-to-rotor diameter ratios.