Search

Endowing robots with reversible phase transition ability, especially between elastomer and fluid states, can significantly broaden their functionality and applicability. Limited attempts have been made to realize the reversible elastomer–fluid transition. Existing phase transition materials in robotics have over‐hard (≈4 GPa) or over‐soft (≈4 kPa) stiffness in the solid states, which should be further investigated to perform more compliant motions. To address these challenges, a reversible elastomer–fluid transition mechanism enabled by magnetically induced hot melt materials (MIMMs) is presented. The transition principle is explained and material characterizations are conducted. MIMMs‐based metamorphosic robots endow self‐metamorphosing abilities, such as self‐healing, spatial reshaping, self‐division/assembly, and additive manufacturability. When interacting with external environments, MIMMs‐based robots can perform further multifunctional abilities, such as collaborations for structure repairs, swimming by symbiosis with external objects, flowing through a narrow terrain by transiting to fluid, and working with elastomeric structures for stiffness‐variable fluid soft actuators. The proposed elastomer–fluid transitions open a new path for robots to generate more flexible and metamorphosic motions, thereby addressing the cross‐phase transformation challenges that soft robots face. [ABSTRACT FROM AUTHOR]

This paper introduces a systematical interval-based framework of inherent uncertainties and pose evaluation for a class of soft continuum robots driven by flexible shafts. A more general model of continuum robots driven by shaft tendons is extended from prior kinematic models. On top of the proposed model, the interval-based analysis is presented to analyze and characterize the pose of continuum robots considering uncertainties in kinematic parameters and joint inputs. A 3-D printed bending actuator driven by a flexible shaft is evaluated for case study based on the proposed interval-valued framework. This paper investigates and compares a couple of refinement methods and proposes a new way of sensitivity analysis of model parameters based on interval arithmetic. The kinematic and mechanics parameters are measured and identified experimentally with a representation of intervals. The in-plane motion experiment validates that the computed bounds can enclose all the measured tip positions with consideration of the measurement uncertainty. The method is also validated when external loading is exerted. Note to Practitioners—With the fast development of soft robotics, the increasing number of soft robotic manipulators show great potentials of application in industries such as agriculture, biomedicine, home automation, manufacturing, logistics, and domestic service. Thanks to the mechanical compliance, soft manipulators demonstrate environmental adaptability at the cost of very precise positioning. However, the guaranteed bounds of the reaching range are valuable in order to provide users a good knowledge of the product performance, which is the motivation of this paper. This paper provides not only a method and framework based on interval analysis to evaluate the pose of soft actuators, but also a case study of uncertainty interval characterization procedure which is domain-specific for soft actuators. The presented method framework can be implemented for continuum manipulators and soft actuators as well as any other robotic devices featured by such flexible components. [ABSTRACT FROM AUTHOR]

Data-defect would affect the data quality and the analysis results of data mining. This paper presents a data-defect inspection method with kernel-neighbor-density-change outlier factor (KNDCOF). The definition of kernel neighbor density is proposed to represent the density of each object in database, and the ascending distance series (ADS) of each object is calculated based on the kernel distance between the object and its neighbors. Then, the average density fluctuation (ADF) of the object is established according to the weighted sum of the square of density difference between the object and others in ADS. Finally, the KNDCOF of the object is equal to the ratios of the ADF of the object and the average ADF of neighbors of the object. The degree of the object being an outlier is indicated by the KNDCOF value. The experiments are performed on three real data sets to evaluate the effectiveness of the proposed method. The experimental results verify that the proposed method has higher quality of data-defect inspection and does not increase the time complexity.

Note to Practitioners–Data-defect inspection is an important procedure of data preprocessing for a real industrial process. This paper presents a data-defect inspection method with kernel-neighbor-density-change outlier factor to identify the outliers, and addresses the challenges associated with the strong correlation and the nonlinearity of the industrial data. The proposed method calculates the outlier factor for each object, which quantifies how outlying it is. The outlier factor is based on the density difference between the object and its neighbors. The larger the outlier factor of an object is, the higher the outlierness of the object is. The proposed method could be wildly used in an industrial complex data set with different density regions. In the industrial field, engineers can deal with the objects with high outlier factor values based on the actual requirements. [ABSTRACT FROM AUTHOR]

Magnetically responsive elastomers generate continuous motions and locomotion through changes in external magnetic fields. The magnetic particles in an elastomer achieve shape‐morphing, but overall structural integrity can be limited by the compliance of elastomers. To overcome this limitation, magnetic elastomers are enhanced with programmable template creases to generate deployable structures as a library. Current methods to program magnetic domains into actuatable segments use sequential or continuous rasterized magnetization, which is gradual and requires dedicated equipment. To achieve faster magnetic domain programming, template folding for the magnetization process is explored. The crease pattern can reconfigure facets to attain the desired magnetization direction and act as discrete mechanical joints. Crease patterns from the foldable templates allow more variations in robotic kinematics and discretize the deformations. The approach using magnetic elastomers and folding templates as a library can simultaneously program a wide range of deployable mechanisms with inherent crease foldability. Additionally, magnetic responsive robots can encompass bistable actuation imparted from the crease design. Functionalization of magnetic origami structures is demonstrated by imbuing the template material with catalytic properties. These robots have the potential to be deployed from a compact folded form to confined environments, enabling a broader spectrum of minimally invasive procedures. [ABSTRACT FROM AUTHOR]

Robot-assisted technologies are overcoming the limitations of the current approaches for transoral surgeries, which are suffering from limited vision and workspace. As a result, we develop a novel teleoperated parallel continuum robot with variable stiffness for collision avoidance. This paper focuses on the feasibility study on a cadaveric model for the robotic system as a first trial. We introduce the configuration of the robotic system, the description of the processes of the trial, including the setting of the robotic system, the test of stiffness, and the action of the manipulation. The contact force between the manipulators with different stiffness and the surrounding tissues and a series of surgical operations of the manipulator, including grasping, cutting, pushing, and pulling tissues under the master-slave control mode, were recorded and analyzed. Experimental results suggest that the typical surgical procedure on a cadaveric model was successfully performed. Moreover, the efficacy and feasibility of the developed robotic system are verified to satisfy the requirements of transoral robotic surgery (TORS). [ABSTRACT FROM AUTHOR]

Oropharyngeal tumor is traditionally resected from an open approach, often necessitating the need of a midline mandibulotomy in order to remove tumor safely with oncologic margins. The limitations imposed by a transoral route include poor visualization of the inferior extent of the oropharynx, rigid instrumentation, and inability to resect tumor that extends caudally into the supraglottis. While visualization with angled endoscopes, coupled with flexible laser development and microscopic magnification may overcome some of these limitations, this technique suffers from linear trajectory of the instruments which hampers expedient surgical resection in a 3-dimensional fashion. With development of the Da Vinci Surgical System, the safety and oncologic feasibility of removing oropharyngeal tumors are made possible because it provides a 3-dimensional magnification of the surgical field and wristed maneuverability of the surgical instruments which enable surgeons to operate around tight anatomical confines. Nevertheless, this first-generation robot is continually being modified with more flexibility and maneuverability through the development of robots like the FLEX Robotic System and more recently the Da Vinci Single Port System (SP). In this review, we will discuss the historic developments of robots for transoral applications, present the current approved robotic systems, and highlight the upcoming robots for transoral robotic surgery (TORS). Finally, we will also propose an ideal TORS surgical robot by highlighting the engineering technologies to accomplish these challenges. [ABSTRACT FROM AUTHOR]

Accurate high-temperature measurement is very important for process monitoring of an industrial system. Infrared thermometers usually can handle no more than 1000 °C and should use some expensive accessories for higher temperature measurements. This paper proposes a low-cost pyrometry system with nonlinear multisense partial least squares (NMSPLS). The ordinary camera with different filters is designed to collect the images of hot object at different wavelengths, and the NMSPLS is presented for predicting the temperature of the hot object from the obtained images. For the proposed method, the obtained images are represented by the multisense tensor, where red, green, and blue are regarded as three different dimensions in a sense of the tensor, respectively. The proposed method integrates an outer model and a nonlinear inner model. For the outer model, the independent variables and the dependent variables are projected into a low-dimensional common latent subspace. The weight matrices are calculated from the independent variables by the tucker decomposition, and the single value decomposition is adopted for extracting the latent variables (Lvs) based on the covariance between the independent variables and the dependent variables. For the nonlinear inner model, the neural network is adopted and the extracted Lvs are used as the input and the output of the neural network, respectively. Two real experiments are performed for estimating the proposed method. The experimental results verify that the proposed method can be applied for pyrometry and have higher effectiveness. [ABSTRACT FROM AUTHOR]

Multirobot comanipulation shows great potential in surpassing the limitations of single-robot manipulation in complicated tasks such as robotic surgeries. However, a dynamic multirobot setup in unstructured environments poses great uncertainties in robot configurations. Therefore, the coordination relationships between the end-effectors and other devices, such as cameras (hand–eye calibration) and tools (tool–flange calibration), as well as the relationships among the base frames (robot–robot calibration) have to be determined timely to enable accurate robotic cooperation for the constantly changing configuration of the systems. We formulated the problem of hand–eye, tool–flange, and robot–robot calibration to a matrix equation \mathbfAXB=YCZ. A series of generic geometric properties and lemmas were presented, leading to the derivation of the final simultaneous algorithm. In addition to the accurate iterative solution, a closed-form solution was also introduced based on quaternions to give an initial value. To show the feasibility and superiority of the simultaneous method, two nonsimultaneous methods were compared through thorough simulations under various robot movements and noise levels. Comprehensive experiments on real robots were also performed to further validate the proposed methods. The comparison results from both simulations and experiments demonstrated the superior accuracy and efficiency of the proposed simultaneous calibration method. [ABSTRACT FROM PUBLISHER]

We propose an efficient and effective magnetic tracking method in this paper. The tracking method is based on tri-axial transmitting coils and uniaxial sensing of the generated electromagnetic field. Three mutually orthogonal transmitting coils are excited simultaneously with alternating current (AC) signals of different frequency. At a specific position, the sum of amplitude square of the three different frequency sensing signals will reach maximum when the uniaxial coil points to the tri-axial transmitting coils. The maximum value is reciprocally proportional to the cube of the distance between the transmitter and receiver. By processing the output signals from the uniaxial sensing coil when it is rotating, the direction and distance between the sensing coil and transmitting coils can be decided with an efficient method with low calculation overheads. Experiments were conducted to validate the proposed method. [ABSTRACT FROM PUBLISHER]