Search results for: hand control

Authors: Ian A. Grout

Abstract:

In this paper, the design and development of a system to provide hand motion and gesture control of laboratory test equipment is considered and discussed. The Leap Motion controller is used to provide an input to control a laboratory power supply as part of an electronic circuit experiment. By suitable hand motions and gestures, control of the power supply is provided remotely and without the need to physically touch the equipment used. As such, it provides an alternative manner in which to control electronic equipment via a PC and is considered here within the field of human computer interaction (HCI).

Keywords: control, hand gesture, human computer interaction, test equipment

Procedia PDF Downloads 315

Authors: Christopher Spiewak, M. R. Islam, Mohammad Arifur Rahaman, Mohammad H. Rahman, Roger Smith, Maarouf Saad

Abstract:

For those who have lost the ability to move their hand, going through repetitious motions with the assistance of a therapist is the main method of recovery. We have been developed a robotic assistive device to rehabilitate the hand motions in place of the traditional therapy. The developed assistive device (RAD-HR) is comprised of four degrees of freedom enabling basic movements, hand function, and assists in supporting the hand during rehabilitation. We used a nonlinear computed torque control technique to control the RAD-HR. The accuracy of the controller was evaluated in simulations (MATLAB/Simulink environment). To see the robustness of the controller external disturbance as modelling uncertainty (±10% of joint torques) were added in each joints.

Keywords: biorobotics, rehabilitation, robotic assistive device, exoskeleton, nonlinear control

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Authors: Emre Akyürek, Anthony Huynh, Tatiana Kalganova

Abstract:

The Ambidextrous Robot Hand is a robotic device with the purpose to mimic either the gestures of a right or a left hand. The symmetrical behavior of its fingers allows them to bend in one way or another keeping a compliant and anthropomorphic shape. However, in addition to gestures they can reproduce on both sides, an asymmetrical mechanical design with a three tendons routing has been engineered to reduce the number of actuators. As a consequence, control algorithms must be adapted to drive efficiently the ambidextrous fingers from one position to another and to include grasping features. These movements are controlled by pneumatic muscles, which are nonlinear actuators. As their elasticity constantly varies when they are under actuation, the length of pneumatic muscles and the force they provide may differ for a same value of pressurized air. The control algorithms introduced in this paper take both the fingers asymmetrical design and the pneumatic muscles nonlinearity into account to permit an accurate control of the Ambidextrous Robot Hand. The finger motion is achieved by combining a classic PID controller with a phase plane switching control that turns the gain constants into dynamic values. The grasping ability is made possible because of a sliding mode control that makes the fingers adapt to the shape of an object before strengthening their positions.

Keywords: ambidextrous hand, intelligent algorithms, nonlinear actuators, pneumatic muscles, robotics, sliding control

Procedia PDF Downloads 296

Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

Abstract:

Vision based user interfaces to control TVs and PCs have the advantage of being able to perform natural control without being limited to a specific device. Accordingly, various studies on hand gesture recognition using RGB cameras or depth cameras have been conducted. However, such cameras have the disadvantage of lacking in accuracy or the construction cost being large. The proposed method uses a low cost IR camera to accurately differentiate between the hand and the background. Also, complicated learning and template matching methodologies are not used, and the correlation between the fingertips extracted through curvatures is utilized to recognize Click and Move gestures.

Keywords: recognition, hand gestures, infrared camera, RGB cameras

Procedia PDF Downloads 405

Authors: Jozsef Katona, Attila Kovari, Tibor Ujbanyi, Gergely Sziladi

Abstract:

By the development of IT systems, human-computer interaction is also developing even faster and newer communication methods become available in human-machine interaction. In this article, the application of a hand gesture controlled human-computer interface is being introduced through the example of a mobile robot. The control of the mobile robot is implemented in a realistic virtual environment that is advantageous regarding the aspect of different tests, parallel examinations, so the purchase of expensive equipment is unnecessary. The usability of the implemented hand gesture control has been evaluated by test subjects. According to the opinion of the testing subjects, the system can be well used, and its application would be recommended on other application fields too.

Keywords: human-machine interface (HCI), mobile robot, hand control, virtual environment

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Authors: Sanu Muhammed C., Nihal Vadakkan, Sahil Athrij, Sasi Gopalan

Abstract:

Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards AR/VR applications, the user experience on these devices should be considered, and we are trying to improve user experience in VR. This paper proposes a survey-based solution to improve user experience in VR. By creating a VR environment where users can move a ball from one position to another using a remote controller and another VR environment where users can move a ball from one place to another using hand gestures/ By allowing a set of audience to use these two environments, we can get their feedback. There are two steps in this comparison, 1) Using Hand Gestures To Move Ball In VR Environment: Here, we create a VR environment where two baskets are there, and one ball will be there in a basket. Here users can transfer the ball to another basket using hand gestures. They will be able to move the ball using hand gestures. 2) Using Remote Control To Move Ball In VR Environment: Here, we create a VR environment where two baskets are there, and one ball will be there in a basket. Here users can transfer the ball to another basket using a remote control. They will be able to move the ball using a remote controller. The above two environments are given to users to experience, and their responses will be recorded to compare the user experience in the above two environments.

Keywords: virtual reality, user experience, hand gestures, remote control

Procedia PDF Downloads 145

Authors: Chen-Sheng Chen, Tsung-Yi Huang, Pi-Chang Sun

Abstract:

Chronic stroke patients often have complaints about hand dysfunction due to flexor hypertonia and extensor weakness, which makes it difficult to open their affected hand for functional grasp. Hand rehabilitation after stroke is essential for restoring functional independence. Constraint-induced movement therapy has shown to be a successful treatment for patients who have acquired certain level of wrist and finger extension. The goal of this study was to investigate the feasibility of task-oriented approach incorporating 3D-printed dynamic hand device by evaluating hand functional performance. This study manufactured a hand device using 3d printer for chronic stroke. The experimental group engaged task-oriented approach with dynamic hand device, but the control group only received task-oriented approach. Outcome measurements include palmar pinch force (PPF), lateral pinch force (LPF), grip force (GF), and Box and Blocks Test (BBT). The results of study revealed the improvement of PPF in experimental group but not in control group. Meanwhile, improvement in LPF, GF and BBT can be found in both groups. This study demonstrates that the 3D-printed dynamic hand device is an effective therapeutic assistive device to improve pinch force, grasp force, and dexterity and facilitate motivation during home program in individuals with chronic stroke.

Keywords: 3D printing, biomechanics, hand orthosis, stroke

Procedia PDF Downloads 267

Authors: Dev Pratap Singh, Harshika Hasija, Ashwini S.

Abstract:

The project aims to provide a touchless, intuitive interface for human-computer interaction, enabling users to control their computers using hand gestures and voice commands. The system leverages advanced computer vision techniques using the Media Pipe framework and OpenCV to detect and interpret real-time hand gestures, transforming them into mouse actions such as clicking, dragging, and scrolling. Additionally, the integration of a voice assistant powered by the speech recognition library allows for seamless execution of tasks like web searches, location navigation, and gesture control in the system through voice commands.

Keywords: gesture recognition, hand tracking, machine learning, convolutional neural networks, natural language processing, voice assistant

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Authors: K. Prabhu, K. Dinesh, M. Ranjani, M. Suhitha

Abstract:

During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the five gestures will be detected when shown with their hands via the webcam, which is placed for gesture detection. The personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: nodeMCU, AI technology, gesture, patient

Procedia PDF Downloads 166

Authors: Keerthana E., Lohithya S., Harshavardhini K. S., Saranya G., Suganthi S.

Abstract:

In an epoch of expanding human-machine interaction, the development of innovative interfaces that bridge the gap between physical gestures and digital control has gained significant momentum. This study introduces a distinct solution that leverages a combination of MEMS (Micro-Electro-Mechanical Systems) sensors, an Arduino Mega microcontroller, and a PC to create a hand gesture interface for PC control and SMS notification. The core of the system is an ADXL335 MEMS accelerometer sensor integrated with an Arduino Mega, which communicates with a PC via a USB cable. The ADXL335 provides real-time acceleration data, which is processed by the Arduino to detect specific hand gestures. These gestures, such as left, right, up, down, or custom patterns, are interpreted by the Arduino, and corresponding actions are triggered. In the context of SMS notifications, when a gesture indicative of a new SMS is recognized, the Arduino relays this information to the PC through the serial connection. The PC application, designed to monitor the Arduino's serial port, displays these SMS notifications in the serial monitor. This study offers an engaging and interactive means of interfacing with a PC by translating hand gestures into meaningful actions, opening up opportunities for intuitive computer control. Furthermore, the integration of SMS notifications adds a practical dimension to the system, notifying users of incoming messages as they interact with their computers. The use of MEMS sensors, Arduino, and serial communication serves as a promising foundation for expanding the capabilities of gesture-based control systems.

Keywords: hand gestures, multiple cables, serial communication, sms notification

Procedia PDF Downloads 69

Authors: Vedant Vardhan Rathour, Anant Agrawal

Abstract:

The project aims to provide a touchless, intuitive interface for human-computer interaction, enabling users to control their computer using hand gestures and voice commands. The system leverages advanced computer vision techniques using the MediaPipe framework and OpenCV to detect and interpret real time hand gestures, transforming them into mouse actions such as clicking, dragging, and scrolling. Additionally, the integration of a voice assistant powered by the Speech Recognition library allows for seamless execution of tasks like web searches, location navigation and gesture control on the system through voice commands.

Keywords: gesture recognition, hand tracking, machine learning, convolutional neural networks

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

Abstract:

Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

Procedia PDF Downloads 306

Authors: Ajeevan Gautam, Gulam Anwer Khan, Pratibha Pokhrel

Abstract:

Introduction: Dermatoglyphics is the science which deals with the study of dermal ridge configuration on the digits, palms and soles. It is grooved by ridges and forms variety of configurations. The aim of the study was to identify dermal ridge patterns on fingertip of hypertensive patients and in normal population and to compare patterns among them. Methods: The subjects of the study were 130 hypertensives and 130 non-hypertensives cases of Kathmandu Valley aged between 40 to 80 years. Case history was recorded after consent finger prints were taken. Different parameters as whorl, loop, arch and composite patterns were studied and analysed. Result: It revealed, increased whorl pattern in hypertensive. It showed 65.69% whorl, 29.23% loop and 5.07% arch patterns in right hand of hypertensive people. In control, it was found to be 34.46% whorl, 58.15% loop and 5.38% arch patterns respectively. Similarly in left hand 63.69% whorl, 32% loop and 4.30% arch in hypertensive group. In control group it was 60.15% as loop, 35.69% as whorl and 15% as arch. Discussion: Based on findings of the result, it was concluded that the whorl, loop and arch patterns observed as 65.69%, 29.23% and 5.07% respectively in hypertensive cases in right hand. Similarly in left hand, it was found to be 4.30% as arch, 32% as loop and 63.69% as whorl patterns, but in normotensive subjects these patterns were recorded as 36.43%, 58.15%, 5.38% in right hand and 35.69%, 60.15%, 4.15% in left hand as whorl, loop and arch respectively.

Keywords: arch, dermatoglyphics, hypertension, loop, whorl

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Authors: Jun-ya Nagase, Toshiyuki Satoh, Norihiko Saga, Koichi Suzumori

Abstract:

In recent years, Japanese society has been aging, engendering a labour shortage of young workers. Robots are therefore expected to perform tasks such as rehabilitation, nursing elderly people, and day-to-day work support for elderly people. The pneumatic balloon actuator is a rubber artificial muscle developed for use in a robot hand in such environments. This actuator has a long stroke, and a high power-to-weight ratio compared with the present pneumatic artificial muscle. Moreover, the dynamic characteristics of this actuator resemble those of human muscle. This study evaluated characteristics of force control of balloon actuator using a predictive functional control (PFC) system with disturbance observer. The predictive functional control is a model-based predictive control (MPC) scheme that predicts the future outputs of the actual plants over the prediction horizon and computes the control effort over the control horizon at every sampling instance. For this study, a 1-link finger system using a pneumatic balloon actuator is developed. Then experiments of PFC control with disturbance observer are performed. These experiments demonstrate the feasibility of its control of a pneumatic balloon actuator for a robot hand.

Keywords: disturbance observer, pneumatic balloon, predictive functional control, rubber artificial muscle

Procedia PDF Downloads 452

Authors: M. J. Shofa, A. Hidayatno, O. M. Armand

Abstract:

MRP as a production control system is appropriate for the deterministic environment. Unfortunately, most production systems such as customer demands are stochastic. Demand-Driven MRP (DDMRP) is a new approach for inventory control system, and it deals with demand uncertainty. The objective of this paper is to compare the MRP and DDMRP work for a long lead time and uncertain demand in terms of on-hand inventory levels. The evaluation is conducted through a discrete event simulation using purchased part data from an automotive company. The result is MRP gives 50,759 pcs / day while DDMRP gives 34,835 pcs / day (reduce 32%), it means DDMRP is more effective inventory control than MRP in terms of on-hand inventory levels.

Keywords: Demand-Driven MRP, long lead time, MRP, uncertain demand

Procedia PDF Downloads 301

Authors: P. Revathi, T. Mrunalini, K. Padma Priya, P. Ramya, R. Saranya

Abstract:

During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the 5 gestures will be detected when shown with their hands via a webcam which is placed for gesture detection. A personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: onion harvesting, automatic pluging, camera, raspberry pi

Procedia PDF Downloads 198

Authors: Y. Y. Pang, N. A. Ismail

Abstract:

The map is a powerful and convenient tool in helping us to navigate to different places, but the use of indirect devices often makes its usage cumbersome. This study intends to propose a new map navigation dialogue that uses hand gesture. A set of dialogue was developed from users’ perspective to provide users complete freedom for panning, zooming, rotate, and find direction operations. A participatory design experiment was involved here where one hand gesture and two hand gesture dialogues had been analysed in the forms of hand gestures to develop a set of usable dialogues. The major finding was that users prefer one-hand gesture compared to two-hand gesture in map navigation.

Keywords: hand gesture, map navigation, participatory design, intuitive interaction

Procedia PDF Downloads 279

Authors: Cecilia Amponsem-Boateng, Timothy B. Oppong, Haiyan Yang, Guangcai Duan

Abstract:

The human palm has been identified as one of the richest habitats for human microbial accommodation making hand hygiene essential to primary prevention of infection. Since the hand is in constant contact with fomites which have been proven to be mostly contaminated, building hand hygiene habits is essential for the prevention of infection. This research was conducted to assess the hand hygiene habits of Ghanaian youths in Accra. This study used a survey as a quantitative method of research. The findings of the study revealed that out of the 254 participants who fully answered the questionnaire, 22% had the habit of washing their hands after outings while only 51.6% had the habit of washing their hands after using the bathroom. However, about 60% of the participants said they sometimes ate with their hands while 28.9% had the habit of eating with the hand very often, a situation that put them at risk of infection from their hands since some participants had poor handwashing habits; prompting the need for continuous education on hand hygiene.

Keywords: hand hygiene, hand hygiene habit, hand washing, hand sanitizer use

Procedia PDF Downloads 107

Authors: M. Jebali, M. Jemni

Abstract:

This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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Authors: Linghui Meng, James Atlas, Deborah Munro

Abstract:

There is an increasing demand for prosthetics capable of mimicking natural limb movements and hand gestures, but precise movement control of prosthetics using only electrode signals continues to be challenging. This study considers the implementation of machine learning as a means of improving accuracy and presents an initial investigation into hand gesture recognition using models based on electromyographic (EMG) signals. EMG signals, which capture muscle activity, are used as inputs to machine learning algorithms to improve prosthetic control accuracy, functionality and adaptivity. Using logistic regression, a machine learning classifier, this study evaluates the accuracy of classifying two hand gestures from the publicly available Ninapro dataset using two-time series feature extraction algorithms: Time Series Feature Extraction (TSFE) and Convolutional Neural Networks (CNNs). Trials were conducted using varying numbers of EMG channels from one to eight to determine the impact of channel quantity on classification accuracy. The results suggest that although both algorithms can successfully distinguish between hand gesture EMG signals, CNNs outperform TSFE in extracting useful information for both accuracy and computational efficiency. In addition, although more channels of EMG signals provide more useful information, they also require more complex and computationally intensive feature extractors and consequently do not perform as well as lower numbers of channels. The findings also underscore the potential of machine learning techniques in developing more effective and adaptive prosthetic control systems.

Keywords: EMG, machine learning, prosthetic control, electromyographic prosthetics, hand gesture classification, CNN, computational neural networks, TSFE, time series feature extraction, channel count, logistic regression, ninapro, classifiers

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Authors: Waqar Ahmad Bajwa

Abstract:

In the land market, there are two kinds of government intervention. First one is the control of development and second is the supply of land. In the both intervention Government has a lot of benefits. In development control the government designation of conservation areas and the effects of growth controls which may increase the price of land. On other hand Government also apply charge fee on land. The second type of intervention is to increase the supply of land, either by direct action or indirect action, as in the Pakistan, by obligatory purchase or important domain.

Keywords: supply of control, control of development, charge fee, land control

Procedia PDF Downloads 264

Authors: Sung-Wook Shin, Sung-Taek Chung

Abstract:

Hand grip strength has been utilized as an indicator to evaluate the motor ability of hands, responsible for performing multiple body functions. It is, however, difficult to evaluate other factors (other than hand muscular strength) utilizing the hand grip strength only. In this study, we analyzed the motor ability of hands using EMG and the hand grip strength, simultaneously in order to evaluate concentration, muscular strength reaction time, instantaneous muscular strength change, and agility in response to visual reaction. In results, the average time (and their standard deviations) of muscular strength reaction EMG signal and hand grip strength was found to be 209.6 ± 56.2 ms and 354.3 ± 54.6 ms, respectively. In addition, the onset time which represents acceleration time to reach 90% of maximum hand grip strength, was 382.9 ± 129.9 ms.

Keywords: hand grip strength, EMG, visual reaction, endurance

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Authors: Faik Derya Ince, Ugur Topgul, Alp Gunay, Can Bayoglu, Dante J. Dorantes-Gonzalez

Abstract:

Explosive attacks are arguably the most lethal threat that may occur in terrorist attacks. In order to counteract this issue, explosive ordnance disposal operators put their lives on the line to dispose of a possible improvised explosive device. Robots can make the disposal process more accurately and saving human lives. For this purpose, there is a demand for more accurate and dexterous manipulating robotic hands that can be teleoperated from a distance. The aim of this project is to design a robotic hand that contains two active and two passive DOF for each finger, as well as a minimum set of tools for mechanical cutting and screw driving within the same robotic hand. Both hand and toolset, are teleoperated from a distance from a haptic robotic glove in order to manipulate dangerous objects such as improvised explosive devices. SolidWorks® Computer-Aided Design, computerized dynamic simulation, and MATLAB® kinematic and static analysis were used for the robotic hand and toolset design. Novel, dexterous and robust solutions for the fingers were obtained, and six servo motors are used in total to remotely control the multi-tooled robotic hand. This project is still undergoing and presents currents results. Future research steps are also presented.

Keywords: Explosive Manipulation, Robotic Hand, Tele-Operation, Tool Integration

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Authors: Rakesh Krishna, Abhishek Poddar

Abstract:

The paper discusses the work carried out on the implementation of control techniques like Digital Pulse Width Modulation (PWM) and Digital Pulse Fired control(PFC). These techniques are often used in devices like inverters, battery chargers, DC-to-DC converters can also be implemented on household devices like heaters. The advantage being the control and improved life span of device. In case of batteries using these techniques are known to increase the life span of battery in mobiles and other hand-held devices. 8051 microcontroller is used to implement these methods.Thyristors are used for switching operations.

Keywords: PWM, SVM, PFC, bidirectional inverters, snubber

Procedia PDF Downloads 572

Authors: Sebastian van Delden, Matthew Anuszkiewicz, Jayse White, Scott Stolarski

Abstract:

Industrial robotic manipulators have been commonplace in the manufacturing world since the early 1960s, and unmanned aerial vehicles (drones) have only begun to realize their full potential in the service industry and the military. The omnipresence of these technologies in their respective fields will only become more potent in coming years. While these technologies have greatly evolved over the years, the typical approach to human interaction with these robots has not. In the industrial robotics realm, a manipulator is typically jogged around using a teach pendant and programmed using a networked computer or the teach pendant itself via a proprietary software development platform. Drones are typically controlled using a two-handed controller equipped with throttles, buttons, and sticks, an app that can be downloaded to one’s mobile device, or a combination of both. This application-oriented work offers a novel approach to human interaction with both unmanned aerial vehicles and industrial robotic manipulators via hand gestures and movements. Two systems have been implemented, both of which use a Myo™ armband to control either a drone (DJI Spark™) or a robotic arm (Stäubli™ TX40). The methodologies developed by this work present a mapping of armband gestures (fist, finger spread, swing hand in, swing hand out, swing arm left/up/down/right, etc.) to either drone or robot arm movements. The findings of this study present the efficacy and limitations (precision and ergonomic) of hand gesture control of two distinct types of robotic technology. All source code associated with this project will be open sourced and placed on GitHub. In conclusion, this study offers a framework that maps hand and arm gestures to drone and robot arm control. The system has been implemented using current ubiquitous technologies, and these software artifacts will be open sourced for future researchers or practitioners to use in their work.

Keywords: human robot interaction, drones, gestures, robotics

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Authors: Evan Lowhorn, Rocio Alba-Flores

Abstract:

Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

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Authors: Yusuke Kuramitsu, Tomoaki Hashimoto, Hirokazu Tahara

Abstract:

The control problem of underactuated spacecrafts has attracted a considerable amount of interest. The control method for a spacecraft equipped with less than three control torques is useful when one of the three control torques had failed. On the other hand, the quantized control of systems is one of the important research topics in recent years. The random dither quantization method that transforms a given continuous signal to a discrete signal by adding artificial random noise to the continuous signal before quantization has also attracted a considerable amount of interest. The objective of this study is to develop the control method based on random dither quantization method for stabilizing the rotational motion of a rigid spacecraft with two control inputs. In this paper, the effectiveness of random dither quantization control method for the stabilization of rotational motion of spacecrafts with two torque inputs is verified by numerical simulations.

Keywords: spacecraft control, quantized control, nonlinear control, random dither method

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Authors: Keyi Wang

Abstract:

Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Badr M. Alshammari, Mohamed A. Khlifi

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This paper presents the analysis of DC/DC converter including a comparative study of control methods to extract the maximum power and to track the maximum power point (MPP) from photovoltaic (PV) systems under changeable environmental conditions. This paper proposes two methods of maximum power point tracking algorithm for photovoltaic systems, based on the first hand on P&O control and the other hand on the first order IC. The MPPT system ensures that solar cells can deliver the maximum power possible to the load. Different algorithms are used to design it. Here we compare them and simulate the photovoltaic system with two algorithms. The algorithms are used to control the duty cycle of a DC-DC converter in order to boost the output voltage of the PV generator and guarantee the operation of the solar panels in the Maximum Power Point (MPP). Simulation and experimental results show that the proposed algorithms can effectively improve the efficiency of a photovoltaic array output.

Keywords: solar cell, DC/DC boost converter, MPPT, photovoltaic system

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Authors: Tamara Grujic, Mirjana Bonkovic

Abstract:

Measurements and quantitative analysis of kinematic parameters of human hand movements have an important role in different areas such as hand function rehabilitation, modeling of multi-digits robotic hands, and the development of machine-man interfaces. In this paper the assessment and evaluation of the reach-to-grasp movement by using computerized and robot-assisted method is described. Experiment involved the measurements of hand positions of seven healthy subjects during grasping three objects of different shapes and sizes. Results showed that three dominant phases of reach-to-grasp movements could be clearly identified.

Keywords: human hand, kinematics, measurement and analysis, reach-to-grasp movement

Procedia PDF Downloads 463