Human-Robot Interaction Based on Gaze Gestures for the Drone Teleoperation

Teleoperation has been widely used to perform tasks in dangerous and unreachable environments by replacing humans with controlled agents. The idea of human-robot interaction (HRI) is very important in teleoperation. Conventional HRI input devices include keyboard, mouse and joystick, etc. However, they are not suitable for handicapped users or people with disabilities. These devices also increase the mental workload of normal users due to simultaneous operation of multiple HRI input devices by hand. Hence, HRI based on gaze tracking with an eye tracker is presented in this study. The selection of objects is of great importance and occurs at a high frequency during HRI control. This paper introduces gaze gestures as an object selection strategy into HRI for drone teleoperation. In order to test and validate the performance of gaze gestures selection strategy, we evaluate objective and subjective measurements, respectively. Drone control performance, including mean task completion time and mean error rate, are the objective measurements. The subjective measurement is the analysis of participant perception. The results showed gaze gestures selection strategy has a great potential as an additional HRI for use in agent teleoperation

Design and model analysis of the sonic vibration head

As a novel environmental sampling technique, sonic vibration drilling has been rapidly developed in the past few years. The penetration force is generated from two eccentric shafts driven by hydraulic motors. This gives rise to the vertical oscillation of the drill pipe to drill in the stratum. As the most important parts of the sonic driller, the vibration head consists of eccentric structure, synchronization mechanism, supporting structure and rotating structure. In the first part of this paper, a 3D mathematical model was developed after analyzing the working law of sonic vibration head by using SolidWork. In the second part, the model was stimulated in order to predict the performances of the sonic vibration head by using ANASYS. In the third part, a physical prototype was developed to conduct practical experiments, confirming feasibility of the previous design and stimulation, and making good references for future optimization

Research and Design of Indoor Parking Guidance System for Urban Traffic

In view of the existing drawbacks of indoor parking guidance system in commercial areas, this paper designs an indoor parking guidance system suitable for urban traffic. The owner first selects the appropriate parking lot through the Mini Program, and reserves a detailed parking space on the Mini Program, and after arriving at the parking lot, the Mini Program performs optimal path planning according algorithm to guide the owner to find the parking space. After arriving at the reserved parking space according to the prompts, the smart parking lock is unlocked by "one-key unlock", and the video detection system observes the parking behavior in real time to avoid the occurrence of illegal parking. At the same time, voice assistants and blind spot guidance facilities are also provided during the induction process to optimize the urban parking guidance system

Development of Downhole Motor Drilling Test Platform

AbstractThe Downhole motor is a kind of important rotary or percussive power drilling tool driven by high pressure mud. Drilling using downhole motor can reduce the energy consumption caused by the friction between long drill string and borehole, and reduce drill pipe wear. In this paper, some important drilling simulation experimental devices around the world have been studied, especially, two kind of drilling simulation experimental devices, the conventional bottom hole experimental device and high temperature and high pressure experimental devices have been analyzed respectively. At home and abroad, the typical drilling simulation devices include ZM-35, LST-10, LMT-I, M150, and Terra Tek, etc.. The characters, structures, principles and experimental methods of these typical simulation devices had been introduced in detail, which provides a reference for developing downhole motor testing and drilling process testing

KINEMATICS ANALYSIS OF CHINESE VAULTING HORSE ATHLETE YANG YAHONG'S ACTION OF "HANDSPRING WITH 90&ORDM-180&ORDM-LAYOUT BACK DOUBLE TWIST"

"Handspring with 90&ordm-180&ordm-layout back double twists" is the new developed kind of action in the women gymnastics championship in recent years. Yang Yahong is the only one that can complete this action. With the method of sports biomechanics, the kinematics characteristic of her action will be analyzed and her advantage and disadvantage will be exposed. The finding shows that her running up is fast, the angle speed of the handspring in the second flight is swift and the pose in space is excellent. However, the amount of time of pushing horse is over long and the height of the 'handspring in the second flight is not enough

An easy iris center detection method for eye gaze tracking system

Iris center detection accuracy has great impact on eye gaze tracking system performance. This paper proposes an easy and efficient iris center detection method based on modeling the geometric relationship between the detected rough iris center and the two corners of the eye. The method fully considers four states of iris within the eye region, i.e. center, left, right, and upper. The proposed active edge detection algorithm is utilized to extract iris edge points for ellipse fitting. In addition, this paper also presents a predicted edge point algorithm to solve the decrease in ellipse fitting accuracy, when part of the iris becomes hidden from rolling into a nasal or temporal eye corner. The evaluated result of the method on our eye database shows the global average accuracy of 94.3%. Compared with existing methods, our method achieves the highest iris center detection accuracy. Additionally, in order to test the performance of the proposed method in gaze tracking, this paper presents the results of gaze estimation achieved by our eye gaze tracking system

OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images

Enhancing the robustness of vision algorithms in real-world scenarios is challenging. One reason is that existing robustness benchmarks are limited, as they either rely on synthetic data or ignore the effects of individual nuisance factors. We introduce OOD-CV, a benchmark dataset that includes out-of-distribution examples of 10 object categories in terms of pose, shape, texture, context and the weather conditions, and enables benchmarking models for image classification, object detection, and 3D pose estimation. In addition to this novel dataset, we contribute extensive experiments using popular baseline methods, which reveal that: 1. Some nuisance factors have a much stronger negative effect on the performance compared to others, also depending on the vision task. 2. Current approaches to enhance robustness have only marginal effects, and can even reduce robustness. 3. We do not observe significant differences between convolutional and transformer architectures. We believe our dataset provides a rich testbed to study robustness and will help push forward research in this area.Comment: Project webpage: https://bzhao.me/ROBIN/, this work is accepted as Oral at ECCV 202