The collaboration between a human driver and an automation system will serve as an effective measure before the autonomous driving technology is fully implemented. To discuss the driving authority between a human driver and an automation system, a novel moving horizon shared steering framework is proposed, in which the controller assists the driver when the vehicle is in danger. First, a potential-hazard analysis is presented based on the potential steering operation error and lane departure distance to predict the degree of a hazard and to determine the driving authority between the human driver and the automation system. Then, the minimum collaborative steering operation is determined using a moving horizon optimisation approach with safety constraints. Thus, the automation system shares steering with the driver protect the vehicle from risks in a non-invasive manner. To demonstrate the effectiveness of the proposed strategy, simulations with different types of drivers and scenarios are conducted. The results of these simulations demonstrate that the proposed approach can enhance the driving ability of drivers with different skill levels in dangerous situations. The approach can also guarantee the safety of the intelligent vehicle to some extent when drivers lose focus for a period of time.

Vehicle automation opens opportunities toward the improvement of people, planet, profit value in applications on distribution centres (DCs). Despite vision and drive for innovation in logistics, the lack of knowledge prevents the application of autonomous applications. Intelligent Truck Applications in Logistics (INTRALOG) contributes to this deficit and generates valuable insights for a future application in public environments. Current operational automated guided truck applications are bound to fixed infrastructure and do neither operate in the public domain nor offer opportunities to do so. Nowadays, in-vehicle intelligent systems are focused on driver support, opening opportunities such as truck platooning. INTRALOG cross-borders on DCs in relatively low-complex traffic environment, bridging the gap between autonomous driving in the public domain. The multi-agent system developed within INTRALOG aligns logistical movements on DCs, controlling single or double articulated container trailers (longer and heavier vehicle) between the public parking area and cross-docks. This study elaborates on the experiments on automated manoeuvring on a DC with single (SAVs) and double articulated vehicles (DAVs). The experiments comply with business requirements, e.g. manoeuvrability, time to dock and positioning accuracy. The research focuses on the effects of these aspects and control strategies of SAVs and DAVs.

Robots were used for the first time in surgery back in 1997. Since then abdominal surgeries ensued with robotic surgery ‘infiltrating’ urology, gynaecology, and thoracic surgery fields as well. Lately, robotic surgery methodologies found application in head and neck surgeries leading to the development of the transoral robotic surgery (TORS). So far TORS has improved work of surgeons dealing with the oropharynx, hypopharynx, larynx, nasopharynx, thyroid, parapharyngeal space and skull areas of the human body. However, with the introduction of such a new efficacious modality, new questions emerge regarding its integration. The purpose of this review is to provide a thorough analysis of the advantages and disadvantages of TORS according to methodologies that have already been applied, along with their economic aspects, surgery processes, benefits compared to conventional surgery techniques, clinical results and any research gaps. Results indicate that TORS technical advantages denote its quality and importance in the field of robotic surgery.

A piezo-actuated self-lifting insect inspired flapping-wing robot is presented. A novel method is presented in the work, which has taken into account the difficulties and the precision of assembly among micro components. Each component is properly designed and reasonably arranged to reduce the assembly difficulties of such insect-scale robot. Specifically, the design of the piezoelectric actuator has taken into account the electrical isolation and assembly issues. The transmission and the airframe are integrated into one component to avoid assembly difficulties. Fibre directions of wing veins are reasonably arranged to possess high strength and stiffness. As a result, this robot, which weighs 84 mg with a wingspan of 35 mm, can generate sufficient thrust to take off with a flapping amplitude approximately ±60° under the resonant wingbeat frequency of 100 Hz.

We've all heard the hype about automated flying vehicles bringing parcels direct to your door. But when will drone delivery on demand get offthe ground in the UK?

An automatic computer vision algorithm that detects individual paper fibres from an image, assesses the possibility of grasping the detected fibres with microgrippers and detects the suitable grasping points is presented. The goal of the algorithm is to enable automatic fibre manipulation for mechanical characterisation, which has traditionally been slow manual work. The algorithm classifies the objects in images based on their morphology, and detects the proper grasp points from the individual fibres by applying given geometrical constraints. The authors test the ability of the algorithm to detect the individual fibres with 35 images containing more than 500 fibres in total, and also compare the graspability analysis and the calculated grasp points with the results of an experienced human operator with 15 images that contain a total of almost 200 fibres. The detection results are outstanding, with fewer than 1% of fibres missed. The graspability analysis gives sensitivity of 0.83 and specificity of 0.92, and the average distance between the grasp points of the human and the algorithm is 220 µm. Also, the choices made by the algorithm are much more consistent than the human choices.

This paper presents a flexure pressure sensor fabricated by means of 3D printing. This sensor combined with a biosimulant artifact from the National Institute of Standards and Technology (NIST) is used to measure the severity of injuries caused in the case of a robot impact with a human. The stiffness matrix is derived for the structure by means of screw theory. A Finite Element (FE) model is constructed to verify the analytical model and obtain the allowable pressure with regard to the yield stress.

Kinematic and dynamic modelling and corresponding control design of a four-wheel-independent steering and four-wheel-independent driving (4WIS4WID) mobile robot are presented in this study. Different from the differential or car-like mobile robot, the 4WIS4WID mobile robot is controlled by four steering and four driving motors, so the control scheme should possess the ability to integrate and manipulate the four independent wheels. A trajectory tracking control scheme is developed for the 4WIS4WID mobile robot, where both non-linear kinematic control and dynamic sliding-mode control are designed. All of the stabilities of the kinematic and dynamic control laws are proved by Lyapunov stability analysis. Finally, the feasibility and validity of the proposed trajectory tracking control scheme are confirmed through computer simulations.

With the launch and development of the Android system, it is urgent to solve its terminal security protection problem. Based on three aspects, i.e., Android features, security architecture and security mechanisms, this paper analyses the security threats and the corresponding risks faced by the terminal from the technical level and management level respectively. Moreover, a security ecosystem architecture based on Android platform is designed reasonably and effectively to regulate the Android management system. The proposed ecosystem is benefit to solve the security problems such as open-source vulnerability and App store management chaos. The achievement of this paper promotes researches of security risk issues positively.

A rapid path planning adaptive optimization algorithm based on fuzzy neural network is proposed for mobile robot in a static unknown environment. In order to solve the limitations of the subjective experience in the fuzzy control and design problems of path planning, conventional neural network is given fuzzy input signals and fuzzy weights by using the membership function and the error cost function of fuzzy control theory. Neural network is constructed from fuzzy rules to accelerate the convergence of FNN, so that the collision-free motion is achieved by combining with the formation control method for mobile robot. Finally, the experiment results show that the robot path planning based on FNN algorithm is faster than other algorithms to finish the task as well as a better controllability and adaptability by the platform of Player/Stage.