Search results

The purpose of this paper is to define and determine quantifiable measurements for head‐tilt and pilot fatigue by detecting and measuring the six degrees of freedom (6DOF) head motion of test subjects performing flight simulation operations.

First, a flight simulator that met the needs of the research project was designed and fabricated. Second, the tracking system was tested and deemed operable through a series of shakedown runs. Then, the head motion of test subjects was detected and measured using infrared technology. Finally, the data collected were used to establish definitions for head‐tilt and pilot fatigue.

Head‐tilt and pilot fatigue were defined and evidence of their presence was observed in the head motion data.

The goal of this research is to reduce aircraft accidents upon landing and take‐off for general, commercial, and military aviation to include unmanned aerial vehicles.

Literature which covers the definition and measurement of a pilot's head motion in flight is unclear. By defining the optokinetic phenomena of head‐tilt and precisely measuring pilot head motion and developing and using tests of pilots based on the results to screen for head‐tilt, the number of land aircraft veering off runways during both landing and takeoff can be reduced. Also, the number of aircraft overshooting the flight deck on an aircraft carrier can be reduced, as well as fewer crashes upon landing of unmanned aerial vehicles.

Autonomous mobile manipulation depends on a lot of effort at various levels. In general, the hardware design is as important as algorithm (or software) design. In particular, the absence of certain capabilities of hardware can seriously affect the feasibility and performance of algorithms. The purpose of this paper is to present work on developing hardware capability for mobile manipulation by low‐cost humanoids (LOCH) humanoid robot.

This paper presents research work on developing the hardware support which enables vision‐guided mobile manipulation realized on top of a biped humanoid robot called LOCH. One important goal which guides the development is to achieve the hardware capability with human‐like dexterity, modularity, functionality, and appearance.

This paper discusses the detail of solutions leading to the realization of the intended hardware capability, focusing in particular on the issues related to mechanism, actuation, distributed sensing, and distributed control of humanoid head, humanoid hands and humanoid arms. Finally, the paper shows the result of the actual prototype, which can be controlled by a remote control station through wireless connection.

In designing a machine, it is common to do motor‐sizing and material selection. Since these are standard procedures, these details are omitted because readers with the training in mechanical engineering should be able to work out such details in order to select the appropriate motors and materials. Also, this paper does not delve into the description of the biped system of LOCH humanoid, because such work requires another long paper in order to reveal major details.

This paper presents the major detail of research efforts toward developing hardware capabilities for achieving autonomous mobile manipulation by LOCH humanoid robot, focusing on three important modules, namely: perception head, human‐like hands, and arms. The uniqueness of this work is twofold. First, LOCH humanoid robot's perception head has the most versatile sensing capabilities, which are fully integrated into a compact and human‐like head. Second, each of LOCH humanoid robot's hands has 14 degrees of freedom, which are realized within a mechanism which is of human‐hand size and shape. In addition, the perception head, humanoid hands and humanoid arms are seamlessly integrated together owing to the adoption of a distributed system which supports networked sensing and control through the use of both control area network bus and transmission control protocol/internet protocol internet.

Underwater shuttle is widely used in scenarios of deep sea transportation and observation. As messages are transmitted via the limited network, high transmission time-delay often leads to information congestion, worse control performance and even system crash. Moreover, due to the nonlinear issues with respect to shuttle’s heading motion, the delayed transmission also brings extra challenges. Hence, this paper aims to propose a co-designed method, for the purpose of network scheduling and motion controlling.

First, the message transmission scheduling is modeled as an optimization problem via adaptive genetic algorithm. The initial transmission time and the genetic operators are jointly encoded and adjusted to balance the payload in network. Then, the heading dynamic model is compensated for the delayed transmission, in which the parameters are unknown. Therefore, the adaptive sliding mode controller is designed to online estimate the parameters, for enhancing control precision and anti-interference ability. Finally, the method is evaluated by simulation.

The messages in network are well scheduled and the time delay is thus reduced, which increases the quality of service in network. The unknown parameters are estimated online, and the quality of control is enhanced. The control performance of the shuttle control system is thus increased.

The paper is the first to apply co-design method of message scheduling and attitude controlling for the underwater unmanned vehicle, which enhaces the control performance of the network control system.

Programming a multi‐axis robotic device to follow complex contours can be difficult and time consuming. A United States University working with the automotive division of a US company has evolved a prototype system utilising a capacitive displacement transducer.

A binaural sonar sensor for blind persons which models the bat sonar is described. System performance with field plots are presented along with signal analysis on objects forming targets. The distal spatial resolution is little more than one wavelength at the lowest frequency of 50 kHz. The operating bandwidth is 50 kHz producing the power to discriminate between objects. Distance and direction information is obtained over a field of view of 50 degrees within one frequency sweep. Blind persons have demonstrated mobility akin to sighted mobility. This knowledge is of value in designing robots.

THE high cost of producing modern aircraft is underlined by the installation at British Aerospace, Hatfield, of two computer‐controlled machines, costing £2 million, for producing just one of the components for the new Airbus range.

Omnidirectional mobile platforms are still plagued by the problem of heading deviation. In four-Mecanum-wheel systems, this problem arises from the phenomena of dynamic imbalance and slip of the Mecanum wheels while driving. The purpose of this paper is to analyze the mechanism of omnidirectional motion using Mecanum wheels, with the aim of enhancing the heading precision. A proportional-integral-derivative (PID) setting control algorithm based on a radial basis function (RBF) neural network model is introduced.

In this study, the mechanism of omnidirectional motion using Mecanum wheels is analyzed, with the aim of enhancing the heading precision. A PID setting control algorithm based on an RBF neural network model is introduced. The algorithm is based on a kinematics model for an omnidirectional mobile platform and corrects the driving heading in real time. In this algorithm, the neural network RBF NN2 is used for identifying the state of the system, calculating the Jacobian information of the system and transmitting information to the neural network RBF NN1.

The network RBF NN1 calculates the deviations ?Kp, ?Ki and ?Kd to regulate the three coefficients Kp, Ki and Kd of the heading angle PID controller. This corrects the driving heading in real time, resolving the problems of low heading precision and unstable driving. The experimental data indicate that, for a externally imposed deviation in the heading angle of between 34º and ∼38°, the correction time for an omnidirectional mobile platform applying the algorithm during longitudinal driving is reduced by 1.4 s compared with the traditional PID control algorithm, while the overshoot angle is reduced by 7.4°; for lateral driving, the correction time is reduced by 1.4 s and the overshoot angle is reduced by 4.2°.

In this study, the mechanism of omnidirectional motion using Mecanum wheels is analyzed, with the aim of enhancing the heading precision. A PID setting control algorithm based on an RBF neural network model is introduced. The algorithm is based on a kinematics model for an omnidirectional mobile platform and corrects the driving heading in real time. In this algorithm, the neural network RBF NN2 is used for identifying the state of the system, calculating the Jacobian information of the system and transmitting information to the neural network RBF NN1. The method is innovative.

Concentration is the key to safer driving. Ideally, drivers should focus mainly on front views and side mirrors. Typical distractions are eating, drinking, cell phone use, using and searching things in car as well as looking at something outside the car. In this paper, distracted driving detection algorithm is targeting on nine scenarios nodding, head shaking, moving the head 45° to upper left and back to position, moving the head 45° to lower left and back to position, moving the head 45° to upper right and back to position, moving the head 45° to lower right and back to position, moving the head upward and back to position, head dropping down and blinking as fundamental elements for distracted events. The purpose of this paper is preliminary study these scenarios for the ideal distraction detection, the exact type of distraction.

The system consists of distraction detection module that processes video stream and compute motion coefficient to reinforce identification of distraction conditions of drivers. Motion coefficient of the video frames is computed which follows by the spike detection via statistical filtering.

The accuracy of head motion analyzer is given as 98.6 percent. With such satisfactory result, it is concluded that the distraction detection using light computation power algorithm is an appropriate direction and further work could be devoted on more scenarios as well as background light intensity and resolution of video frames.

The system aimed at detecting the distraction of the public transport driver. By providing instant response and timely warning, it can lower the road traffic accidents and casualties due to poor physical conditions. A low latency and lightweight head motion detector has been developed for online driver awareness monitoring.

Current single head pick and place robots have reached their practical limit for throughput rates due to impractical speeds and acceleration, which often damage or lose the product being transferred. The purpose of this paper is to present a new system which uses 2 XY motion slides and an indexing flexible conveyor to achieve a more desired motion while achieving a high throughput rate.

An innovative robotic pick and place motion design (the FlowBot) was previously created to address the changing needs of the packaging and automation industry. A full patent has been filed covering this technology. This paper documents a refinement to the FlowBot concept that produces a more compact implementation, entitled the Compact FlowBot.

Tit was found that the motion of smaller steps with limited accelerations does produce higher throughputs without the excessive accelerations that Delta robots produce. The robotics system does require limited Z height so the potential for multiple stacked systems is presented.

This novel robot has been found to be a next generation design, which has been confirmed by an international patent search. Many established consumer packaging goods companies and food processing companies have lauded its merits. The system needs to move into prototype and full development mode.

The purpose of this paper is to present a novel non-contact method of using head movement to control software without the need for wearable devices.

A webcam and software are used to track head position. When the head is moved through a virtual target, a keystroke is simulated. The system was assessed by participants with impaired mobility using Sensory Software’s Grid 2 software as a test platform.

The target user group could effectively use this system to interact with switchable software.

Physical head switches could be replaced with virtual devices, reducing fatigue and dissatisfaction.

Using a webcam to control software using head gestures where the participant does not have to wear any specialised technology or a marker. This system is shown to be of benefit to motor impaired participants for operating switchable software.