关键词： 3D printing   Sensor   Robotics   Piezoelectric  

摘要： Three-dimensional (3D) printing has become an important fabrication method for soft robotics, due to its ability to make complex 3D structures from computer designs in simple steps and multimaterial co-deposition ability. In this article, the application of 3D printing techniques in the fabrication of four types of tactile sensors commonly used in soft robotics, including the piezoresistive tactile sensor, capacitive tactile sensor, piezoelectric tactile sensor, and triboelectric tactile sensor, will be discussed. The 3D printing mechanism, material, and structure for each type of sensor will be introduced, and the perspectives on the future potential of 3D printable tactile sensors will be discussed.

关键词： Programming   Sense-reason-act   Robotics   Computational thinking   Mathematics   Self-efficacy  

摘要： This study investigates the development of algorithmic thinking as a part of computational thinking skills and self-efficacy of primary school pupils using programmable robots in different instruction variants. Computational thinking is defined in the context of twenty-first century skills and describes processes involved in (re)formulating a problem in a way that a computer can process it. Programming robots offers specific affordances as it can be used to develop programs following a Sense-Reason-Act (SRA) cycle. The literature provides evidence that programming robots has the potential to enhance algorithmic thinking as a component of computational thinking. Specifically there are indications that pupils who use SRA-programming learn algorithmic skills better and achieve a higher level of self-efficacy in an open, scaffold learning environment than through direct instruction. In order to determine the influence of the instruction variant used, an experimental research design was made in which pupils solved algorithm-based mathematical problems (grid diagrams) in a preliminary measurement and their self-efficacy determined via a questionnaire. As an intervention, pupils learn to solve programming issues in pairs using "Lego NXT" robots and "Mindstorms" software in two instruction variants. The post-measurement consists of a Lego challenge, solving mathematical problems (grid diagrams), and a repeated self-efficacy questionnaire. This research shows an increase of our measures on algorithmic thinking dependent on the amount of SRA usage (though not significant). Programming using the SRA-cycle can be considered as the cause of the measured effect. The instruction variant used during the robotic intervention seems to play only a marginal role.

关键词： Nanotechnology   Artificial intelligence   Automation   Personalised medicine   Microfluidics  

摘要： The field of nanotechnology and personalised medicine is undergoing drastic changes in the approach and efficiency of experimentation. The COVID-19 pandemic has spiralled into mass stagnation of major laboratories around the globe and led to increased investment into remote systems for nanoparticle experiments. A significant number of laboratories now operate using automated systems;however, the extension to nanoparticle preparation and artificial intelligence-dependent databases holds great translational promise. The strive to combine automation with artificial intelligence (AI) grants the ability to optimise targeted therapeutic nanoparticles for unique cell types and patients. In this perspective, the current and future trends of automated approaches to nanomedicine synthesis are discussed and compared with traditional methods.

关键词： Simulation   Modeling   Analytical models  

摘要： To Perform reliably and consistently over sustained periods of time, large-scale automation critically relies on computer simulation. Simulation allows us and supervisory AI to effectively design, validate, and continuously improve complex processes, and helps practitioners to gain insight into the operation and justify future investments. While numerous successful applications of simulation in industry exist, such as circuit simulation, finite element methods, and computeraided design (CAD), state-of-the-art simulators fall short of accurately modeling physical phenomena, such as friction, impact, and deformation.

关键词： Dynamic Neural Field   Neural integrator   Assembly robot   Value-based decision making   Sequence learning  

摘要： Modern manufacturing and assembly environments are characterized by a high variability in the built process which challenges human-robot cooperation. To reduce the cognitive workload of the operator, the robot should not only be able to learn from experience but also to plan and decide autonomously. Here, we present an approach based on Dynamic Neural Fields that apply brain-like computations to endow a robot with these cognitive functions. A neural integrator is used to model the gradual accumulation of sensory and other evidence as time-varying persistent activity of neural populations. The decision to act is modeled by a competitive dynamics between neural populations linked to different motor behaviors. They receive the persistent activation pattern of the integrators as input. In the first experiment, a robot learns rapidly by observation the sequential order of object transfers between an assistant and an operator to subsequently substitute the assistant in the joint task. The results show that the robot is able to proactively plan the series of handovers in the correct order. In the second experiment, a mobile robot searches at two different workbenches for a specific object to deliver it to an operator. The object may appear at the two locations in a certain time period with independent probabilities unknown to the robot. The trial-by-trial decision under uncertainty is biased by the accumulated evidence of past successes and choices. The choice behavior over a longer period reveals that the robot achieves a high search efficiency in stationary as well as dynamic environments.

关键词： Contact force estimation   Floating-base space robots   Nonlinear observer   Collision detection and isolation  

摘要： In this paper, the contact force detection, isolation and estimation problems for an orbital robot are addressed. First, an observer based on a base-joints dynamics is reviewed and analyzed considering the issues related to a space robotic application. Then, a new scheme is derived reformulating the dynamics in terms of the motion of the centroid of the whole robot and the joints. In both observers, three momentum-based residuals are defined, which can be used to reconstruct the external contact wrench. The reconstruction through the proposed observer turns out to provide superior performance with respect to the base-joints one thanks to the decoupling of the angular and joint momentum residuals from the spacecraft linear velocity, which is an inaccurate measurement in real space scenarios. The advantages of the proposed observer are shown through both simulative and hardware validation featuring a 7 degrees of freedom (DoF) arm mounted on a 6 DoF moving base.

关键词： innovation   oropharyngeal carcinoma   robotic surgery   transoral endoscopic head and neck surgery  

摘要： Purpose of review As the molecular basis of head and neck cancer becomes more clearly defined, precision medicine has gradually refined the multidisciplinary treatment paradigm for patients with oropharyngeal cancer. Although precision medicine is often thought to refer to new molecular diagnostics or unique medical therapy, the recent adoption of robotic surgery has ushered in the era of 'precision' head and neck surgery. Recent findings Surgeons now routinely utilize a virtual reality environment to reduce the morbidity of head and neck surgical care and improve oncologic and functional outcomes. The development and subsequent FDA approval of the da Vinci SP system, a single-arm system with a flexible camera, has allowed for improved visualization and access to the deep oropharynx and larynx. Groups investigating anti-EGFR antibodies tagged with fluorescent dye as well as inherent autofluorescence differences between normal and cancerous mucosal tissues show promise for improving positive surgical margin rates. The evolution of robotics and visualization for oropharyngeal cancer represents a novel and innovative utilization of new technology to improve care. Further advancements in techniques, from refinement of the robotic platform itself, to novel real-time tumour imaging options will be critical to further advance precision care for these patients.

关键词： Secondary education   Spatial thinking   STEM   Educational robotics   Interactive learning environments  

摘要： Robotics technology has gained significance in educational environments in recent years. Educational robotics provide students with the opportunity to collaborate in science, technology, engineering and mathematics (STEM) oriented activities. This study aims to examine the effects of robotics training on children's spatial ability and attitude toward STEM. A one-group pretest-posttest design, a type of pre-experimental design, was used in the study. The participants were 39 elementary school students (34 boys and 5 girls aged 8-12) who participated in a long-term (31 weeks) robotics course. The course had four main learning objectives related to STEM fields: mechanical design, electronics, algorithms, and robotics programming. The spatial visualization and mental rotation tests were used to determine the children's spatial ability. The STEM attitude scale was used to reveal their attitudes toward science, technology, engineering, mathematics, and related twenty-first century skills. Data were analyzed using t-test and Wilcoxon signed ranks tests. According to the findings, the children's spatial visualization and mental rotation test scores were significantly increased at the end of the course. Moreover, the children's attitudes toward STEM were significantly improved. The results showed that educational robotics may improve children's spatial ability and attitudes toward STEM. The implications of the study were discussed in detail.

关键词： Machine intelligence   Artificial intelligence   Neural networks  

摘要： Purpose For efficient trajectory control of industrial robots, a cumbersome computation for inverse kinematics and inverse dynamics is needed, which is usually developed using spatial transformation using Denavit-Hartenberg principle and Lagrangian or Newton-Euler methods, respectively. The model is highly non-linear and needs to deal with uncertainties because of lack of accurate measurement of mechanical parameters, noise and non-inclusion of joint friction, which results in some inaccuracies in predicting accurate torque trajectories. To get a guaranteed closed form solution, the robot designers normally follow Pieper's recommendation and compromise with the mechanical design. While this may be acceptable for the industrial robots where the aesthetic look is not that important, it is not for humanoid and social robots. To help solve this problem, this study aims to propose an alternative machine learning-based computational approach based on a multi-gated sequence model for finding appropriate mapping between Cartesian space to joint space and motion space to joint torque space. Design/methodology/approach First, the authors generate sufficient data required for the sequence model, using forward kinematics and forward dynamics by running N number of nested loops, where N is the number of joints of the robot. Subsequently, to develop a learning-based model based on sequence analysis, the authors propose to use long short-term memory (LSTM) and hence, train an LSTM model, the architecture details of which have been discussed in the paper. To make LSTM learning algorithms perform efficiently, the authors need to detect and eliminate redundant features from the data set, which the authors propose to do using an elegant statistical tool called Pearson coefficient. Findings To validate the proposed model, the authors have performed rigorous experiments using both hardware and simulation robots (Baxter/Anukul robot) available in their laboratory and KUKA simulation robo