Get Instant Help From 5000+ Experts For
question

Writing: Get your essay and assignment written from scratch by PhD expert

Rewriting: Paraphrase or rewrite your friend's essay with similar meaning at reduced cost

Editing:Proofread your work by experts and improve grade at Lowest cost

And Improve Your Grades
myassignmenthelp.com
loader
Phone no. Missing!

Enter phone no. to receive critical updates and urgent messages !

Attach file

Error goes here

Files Missing!

Please upload all relevant files for quick & complete assistance.

Guaranteed Higher Grade!
Free Quote
wave
Methodology

Discuss About The Gesture Recognition Leap Motion Controller.

This research aims to discuss in detail the leap motion sensor, its working ability and also on how it can be designed to fit an exoskeleton mechanical frame. The project discusses on the various methods used to obtain information required for the project. Data used to describe the leap motion sensors, the working in leap motion and also the concept of working in the exoskeleton frame. It also includes the information about how the leap motion sensors are used and exoskeleton frame [2,3,4].

  • Description of leap motion sensor from scholarlyresource
  • Research on working of the leap motion controllers.
  • Research on  the description of the exoskeleton 
  • How leap motion sensors are used to control the exoskeletonframes
  1. Features used to operate exoskeleton
  2. The general setting of the leap motion control
  3. Checking on the allow background apps in the leap motionsensor
  4. Tracking settings used in leap motion sensors in controlling the exoskeleton
  1. Use of algorithm in frames to control thesensors
  2. Graphical representation of the steps used to control thesensors

It describes the report by giving out related information about the study of the work. Description on the instruments used to illustrate the framework of the report. How information is managed, process of collecting the data from various concepts, illustrations of the figures and diagrams describing the statistical data about the project.

  1. Leap Motion Sensor

This is a computerized hardware device that is specifically designed to maintain motions as input and analogs to a computer peripherals and mouse. It a software that is designed for hand tracking in various virtual reality dimension.

This sensor is a controller USB peripheral system that is built and put on a physical computer in a position that ensures it is facing upwards. Also, the controller can be inserted on to a virtual handset.

By utilizing monochromatic IR cameras plus 3 infrared Light-emitting diodes which are a two –lead semiconductor light source that has junction diodes that produce light when activated in a particular system [6]. In this case, the system represents a hemispherical total area to a perimeter of about 1oo centimeters. The Light-emitting diodes often produce a lower quantity of IR light rays and the two cameras installed in the system generate at least 2000 light frames per given time second of a reflected dataset. These rays are then passed in a crucial USB cable up to the main desktop from where the device is evaluated from the different units of the software’s and thus dealing with the algorithm. Here the information from the manufacturer cannot be revealed to the public. This dimension usually incorporates 3D position dataset by putting a clear comparison with the 2D frameworks that are provided [8].

In lesser observations the increased device magnification distinguishes it from Kinect which involves motion sensors and other input devices thus facilitating easy access [9]. Kinect is more convenient to use in the whole body tracking in an open area or free space, in a certain demonstration the leap motion device indicated to perform operations like proper navigation of a website using gestures on maps, high accuracy art drawing and manipulation of critical 3D visual aspects. At first, the leap motion delivered thousands of units to sole developers who aimed to create significant software for the running of the device.

Discussions

For several years the leap motion has been operating smoothly on bringing hand gestures to virtual reality. It is important when a person use hands to move digital objects from one position to the other in a more natural way than using a certain controller. However, in order to accomplish this activity, the user requires strapping one of the developer’s motion sensor peripherals before an existing VR headset which is a little bit solid or heavy [6]. Also, the sensor was still working on the same software designed for desktop Personal Computers; which is a continuation of the period when leap motions were originally focused on the said personal computer system. Currently, the developer company has the ability to take the next leap to another advanced level where it is dealing with Orion, a new hardware component, and software that is specifically designed just for VR.

From the earliest developed hardware prototypes to the current tracking software, the leap motion controller software has advanced in a long way. Individuals have provided lots of questions on how this technology operates identifying how raw sensor data is changed into a more useful information that engineers and developers can use in their system applications.

In this case, a leap motion sensor is usually very simple. The main frame of the device is consequently made up of two cameras and 3 LEDs that has a given distance that locates the whole part of the spectrum in the light [5]. Because of large lenses in the lead motion, the system can be able to conterinteract some of the images with the high resolution. Over many years the device viewing range was limited to 60 cm that is equivalent to 2ft above the leap motion controller. With the introduction of Orion beta software. The viewing range has tremendously increased to roughly 80 centimeters that is equivalent to 2.6 feet constituting the upper distance of that device. This given dimension is often deterred by Light emitting diodes light ray’s propagation through an area because it becomes much difficult to deduce the user's hand position in a 3D angle in front of a particular distance. The light emitting diode has a limitation on the use of the maximum amount of current produced by the USB.

During this time, the reading from the USB initiates information within the memory and then makes significant changes that will lead to huge resolutions [10]. Dataset continuously reflects on through the USB then moves all the way to the software’s contained by the leap motion software’s. Input raw facts within the system changes whole part of the image in the camera and try to make it a bit unique by running it from the left to the right part of the camera in the leap motion. Normally, it most of the systems where different symbols that individuals can view are those that are illuminated directly in the leap motion components.

Working off a leap motion controller

In this case, after the image is streamed directly to the user's host computer, it calls for some solid mathematics approaches. Despite various myths and misunderstanding. The system does not provide an overview.

However, in many cases the system uses complex dataset. Software is present in a certain desktop PC that ensures processing various images. After accounting for background objects for example heads, results are evaluated thus rebuilding   dimension describing on what the whole part of the system was view [10]. After this point, the data is matched by the inputs which track thus producing missing results. Different techniques concerning the filtering concepts tend to be assessed thus enabling temporally consistency within the results provided. Now system provides entire outcome revealed in format with frame series and snapshots that are composed of all monitoring software’s that will give a feedback by adhering to a certain protocol. Leap motion exchanges message with the panel and other web users through a socket interface connected on the computer, for example, web socket and TCP. The native clients direct the data into simple API structures that direct mechanical frame and issues helper functions. Then, the application logic is rounded up into the leap motion input ensuring free interaction with the motion controller device.

An exoskeleton frame involves a complete wearable machine capable of moving and is powered by a system of electric motors, hydraulic systems a pneumatics. It is also powered by a combination of various advanced technologies that allow limb mobility with a high strength and increased endurance level. Some were developed with gait approaches as helpers for the elderly’s as a result of its unique features that were large and heavy in order to cover other available features [12,13,14]. Wearing a visible device cause unwarranted discomfort and awkwardness. Due to this situation, developers have built an active exoskeleton frame that is aimed to help the gait of old individuals. The system is composed of a low-profile design that ensures a less frame which allows it to be worn on lose clothes thus enhancing it to be more comfortable to wear in a certain social or public setting. Three-dimensional human models were put into solid works and carried out specific element analysis and simulations in order thus determining complex aspect with the varying dimensions [15]. Specifications for building the mechanical frame for the exoskeleton is provided. It copes with various shapes of by trying to use different spaces around. It maintains 7 degrees of freedom for all and different limbs on the lower part of the whole body.

The frame was built using solid works 2015 from Assault and the analysis module made for making static relative loads.

Software

In order to design an exoskeleton frame, the material chosen was aluminum metal with a capability of 275MPa. The metal alloys are quite simple in a computer numerical control enabling quick prototyping when getting a less weight than metals such as iron. This particular allowed was taken due to its relatively high yield strength as it also incurred lower costs [11]. It is evident that that for the frame to be small enough, the material needs to be of higher yield strength. Hosing the material to be used made the amount incurred and accessibility to be widely considered to get prototype that is functioning properly. This required all components present to be incorporated using computer numerical control. Even though the cost for CNC s relatively high, the selected material has lower costs that can be machined gradually as compared to other metals.

  • To have the ability to individually supportitself
  • Occupy low volume anddensity
  • Prevent bone and musclecontacts
  • Avoid tight protrusions and indentations in order to be designed and produced through quickprototyping
  • Modular approach consisting of various components that connect through several points which ensures the exoskeleton frame is adaptable to changing body

The exoskeleton was designed through a continuous cyclical development cycle to reach maximum form

A human 3-dimension body was produced through a make Human and incorporated as other parts were analyzed and recorded. With this technique, components were enabled to be fitted nearer to the model.

Leap motion sensors can be handled in different ways within the exoskeleton frame [19]. Leap motion control panel application; The leap motion control panel in most it has the settings, visualizers, and the pause or the resume tracking device. In setting menu, it helps the user to open the panel in the motion control which is within the exoskeleton frame. In visualizer content, there is the launching of the consumer- oriented visualization application which controls the various activities while in the resume tracking in most cases it helps to produce the tracking data within the frame.

  • Static gesture features. These arealways constructed depending on the palm and also the figures with their distances. The distances between the figures would determine their capability on how to operate the exoskeleton frames.
  • Hand circle features they show how palm is used in drawing a circle in controlling the exoskeleton frames. The frames detect the hand and its responses accordingly. One should ensure the hand is not rotating when circling within the exoskeleton

Use of the index swipe and the index key tapping in controlling the exoskeleton frame. For the two index to operate exoskeleton frame, clockwise and anticlockwise movements should be ensured. This boost the control of the frames.

Use of hand interaction. Use of hand to operate the frames is based on rigid body whereby the first option operating the exoskeleton determines how to begin and trying to have an overview of each other. Different shapes such as the use of cubes are designed to indicate the relationship between the objects.

Use of the leap motion sensors setting also helps to control the exoskeleton frame. There are various methods to tackle these settings within the framework. The following are various settings in most of the leap motion sensors.

General setting. In the page of there are the following functions which occur to assist the leap sensors. Helps to check the allow web box which in overall it opens the web socket server and thus helping tracking data to apply for the new applications within the data [24].

Exoskeleton frame

Checking on the allow background apps so as to allow most of the various applications thus can assist in tracking the overall data in most of the focused application within the panel. The sensors to help to check the images thus helping to get the infrared cameras which pose images contained in the leap motion hardware [34]. When most of the applications are not checked, they continue to receive most of the data but the cameras will not be able to get the images as it is recorded in various frames within the exoskeleton.

Checking on the send usage of data icon as it contains the statistics in the most of the leap motions. Also, the general setting contains the check launch in most of the start-up application this helps to launch the control panel application in the frames [31].

Tracking settings. It checks on the robust module thus helping to perform the most of the lighting conditions within the leap motion [18]. Also, there is need to check the auto –orient tracking as it gives the axis which helps to detect most of the views arranged on the opposite sides of the bars within the exoskeleton frames. The leap motion controller in most of the cases falls on the lighting parts as it captures the structured images for at least half a minute.

In each of the controller panel, there are frames which have snapshots. In most cases only hands and also fingers which are recognized within the senses in frames. Most frames have the Id values which in many cases they are skipped when in use. In the computers, the leap motion senses tend to drop frames which are recorded in most of the computer software. When this software's detect the robust mode in order to analyze the IR there are two frames which are which are discussed that is the frame object and the most ID which consecutively produced and it always increases by a factor of two [20].

Getting the data from the frames. Mostly the frame structures tend to describe the access to data in various frames [21]. There are various codes which tend to illustrate the process on how to have the vital objects which are recorded by the leap motion system within the sensors. Most of the objects within the frames are always reads the only type of the object. They are always stored for future use since they tend to be safe and most of them are encoded using the programming techniques such as the C++ programming method [22]. Motion which is twice the standard one [23]. When an object is moved on the screen with adjustments to the hand movement it means that the move should be maintained smooth at the same time the sensors will give the history and also the frames which serve as the functions within the leap motion panel [23].

Using the exoskeleton frame with the call- backs in the system. At most of the time, listeners are used in the leap motion frames to give the controller rates [25]. The controller contains a function which shows when a new frame is available within the panel. Use of the call-backs tends to be difficult because they handle a lot of the task per unit time. Each call-backs contains various threads and therefore being complex to design and different objects depending on the data provided by each thread [26,27]. Most of the problems incurred include the use of the thread and the whole process of updating some of the objects in the sensors. Therefore, to have adequate results it means most of the update should be used to detect threads and too to detect the useful thread within the panel [28]. Thus it shows that in getting most of the leap motion sensors data is always the same as getting the polling controller.

By following the object or the entities across the exoskeleton frames. If the system has the ID for the frame, then it means there must be an object that stands for the frames. The appropriate function will be detected. If it happens that the code cannot be detected there is the return of the special object or key to the system within the exoskeleton frames [29].

-By use of the algorithm [31].

The exoskeleton uses the input method which comprises of the freehand that helps to move over most of the sensors. In the output method, there is a control system that moves with the help of the raspberry pi 3 to the leap motion sensors codes recorded within the objects. The process of using the algorithm follows the following mechanism whereby there is; start, using the check sensors, detection of the leap motion sensors in the system if the detection is based on the hand movement the robot moves on, there is mail appearing to the system and the end step is to stop.

The current exoskeleton designed can be modified effectively to various body times and the content in hip joints constructed to ensure maximum support is provided. In this case, the frame total weight is 9.4 kilograms (Kong & Jeon 2006). The hip supports 3 degrees DOFs, 17 degrees’ abduction, and rotation because of the continuous spherical bearing [33].

The mechanical frame is ported to the Opens in order to make biomechanical kinematics with the available models. This situation has been properly viewed in other research works concerning active exoskeleton frameworks. However, there exist other specifications and modifications that can be used effectively to enable effective advancements. The exoskeleton frame’s do not support flexion. As it is viewed as a natural movement the type of the stand can be designed to give a posture that in most cases is required to be adjusted so as to come with the range of the overall footwear by all people. Since many frames are manufactured with different posture, the exoskeleton frame should be viewed as totally different. This indicates that it should always be provided as a dataset describing the idea of the leap motion. In this manner a proper software need to be used and come with the utmost design that can facilitate the overall function of the system. Direct current in the system should be identified so as to reduce the rate of resistance within the system. This will be provided through keen screening of actuator system which forms a format that be used in the test thus giving the trials for the system components.

References

Potter, L. E., Araullo, J., & Carter, L. (2013, November). The leap motion controller: a view on sign language. In Proceedings of the 25th Australian computer-human interaction conference: augmentation, application, innovation, collaboration (pp. 175-178).  ACM.

Weichert, F., Bachmann, D., Rudak, B., & Fisseler, D. (2013). Analysis of the accuracy and robustness of the leap motion controller. Sensors, 13(5), 6380-6393.

Bachmann, D., Weichert, F., & Rinkenauer Guna, J., Jakus, G.,  Poga?nik, M., Tomaži?, S., & Sodnik, J. (2014). An analysis of the precision and reliability of the leap motion sensor and its suitability for static and dynamic tracking. Sensors, 14(2), 3702-3720.

Lu, W., Tong, Z., & Chu, J. (2016). Dynamic hand gesture recognition with leap motion controller. IEEE Signal Processing Letters, 23(9), 1188-1192.

Bortole, M., Venkatakrishnan, A., Zhu, F., Moreno, J. C., Francisco, G. E., Pons, J. L., & Contreras-Vidal, J. L. (2015). The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study. Journal of neuroengineering and rehabilitation, 12(1), 54.

Fontana, M., Dettori, A., Salsedo, F., & Bergamasco, M. (2009, May). Mechanical design of a novel hand exoskeleton for accurate force displaying. In Robotics and Automation, 2009. ICRA'09. IEEE  International Conference on (pp. 1704- 1709). IEEE.

Kong, K., & Jeon, D. (2006). Design and control of an exoskeleton for the elderly and patients. IEEE/ASME Transactions on mechatronics, 11(4), 428-432.

Lagoda, C., Schouten, A. C., Stienen, A. H., Hekman, E. E., & van der Kooij, H. (2010, September). Design of an electric series elastic actuated joint for robotic gait rehabilitation training. In Biomedical Robotics and Biomechatronics (BioRob), 2010 3rd IEEE RAS and  EMBS International Conference on (pp. 21-26). IEEE.

Murray, S. A., Ha, K. H., Hartigan, C., & Goldfarb, M. (2015). An assistive control approach for a lower-limb exoskeleton to facilitate recovery of walking following stroke. IEEE Transactions on Neural Systems and

Rehabilitation Engineering, 23(3), 441-449.

Coelho, J. C., & Verbeek, F. J. (2014). Pointing task evaluation of leap motion controller in 3D virtual environment. Creating the Difference, 78, 78-85.

Tung, J. Y., Lulic, T., Gonzalez, D. A.,Tran, J., Dickerson, C. R., & Roy, E. A. (2015). Evaluation of a portable markerless finger position capture device: accuracy of the Leap Motion controller in healthy adults. Physiological measurement, 36(5), 1025.

Smeragliuolo, A. H., Hill, N. J., Disla, L., & Putrino, D. (2016). Validation of the Leap Motion Controller using markered motion capture technology. Journal of biomechanics, 49(9), 1742-1750.

Chuan, C. H., Regina, E., & Guardino, C. (2014, December).  American sign language recognition  using  leap  motion   sensor.  In Machine Learning and Applications (ICMLA), 2014 13th International Conference on (pp. 541-544). IEEE.

Marin, G., Dominio, F., & Zanuttigh, P. (2016). Hand gesture recognition with jointly calibrated leap motion and depth sensor.  Multimedia Tools and Applications, 75(22), 14991-15015.

Liu, H., Wei, X., Chai, J., Ha, I., & Rhee, T. (2011, February). Real- time human motion control with a small number of inertial sensors. In Symposium on Interactive 3D Graphics and Games (pp. 133- 140). ACM.

Cui, J., & Sourin, A. (2014, October). Feasibility study on freehand geometric modeling using leap motion in VRML/X3D. In Cyberworlds (CW), 2014 International Conference on (pp. 389- 392). IEEE.

Du, G., Zhang, P., & Liu, X. (2016).

Markerless Human–Manipulator Interface Using Leap Motion With Interval Kalman Filter and Improved Particle Filter. IEEE Transactions on Industrial Informatics, 12(2), 694-704.

Du, G., & Zhang, P. (2015). A markerless human-robot interface using particle filter and Kalman filter for dual robots. IEEE Transactions on Industrial Electronics, 62(4), 2257-2264.

Burdea, G. C., Cioi, D., Kale, A., Janes, W.

E., Ross, S. A., & Engsberg, J. R. (2013). Robotics and gaming to improve ankle strength, motor control, and function in children with cerebral palsy—a case study series. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 21(2), 165-173.

Young, A. J., & Ferris, D. P. (2017). State of the art and future directions for lower limb robotic exoskeletons. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(2), 171-

Field, M., Pan, Z., Stirling, D., & Naghdy, F. (2011). Human motion capture sensors and analysis in robotics. Industrial Robot: An International Journal, 38(2), 163-171.

De Vito, L., Postolache, O., & Rapuano, S. (2014). Measurements and sensors for motion tracking in motor rehabilitation.

Savatekar, M. R. D., & Dum, M. A. (2016). Design Of Control System For Articulated Robot Using Leap Motion Sensor.

Yang, C., Chen, J., & Chen, F. (2016, September). Neural learning enhanced teleoperation control of Baxter robot using IMU based motion capture. In Automation and Computing (ICAC), 2016 22nd International Conference on (pp. 389-394). IEEE.

Shi, G., Wang, Y., & Li, S. (2014). Human Motion Capture System           and its Sensor Analysis. Sensors & Transducers, 172(6), 206.

Y., Jo, I., Lee, J., & Bae, J. (2017,

September). A wearable hand system for virtual reality. In Intelligent Robots and Systems      (IROS),       2017     IEEE/RSJ

International Conference on (pp. 1052- 1057). IEEE.

Dobins, M. K., Rondot, P., Schwartz, K., Shone, E. D., Yokell, M. R., Abshire, K. J.,... & Lovell, S. (2012). U.S. Patent No. 8,217,995. Washington, DC: U.S. Patent and Trademark Office.

Parietti, F., Chan, K. C., Hunter, B., & Asada, H. H. (2015, May). Design and control of supernumerary robotic limbs for balance augmentation. In Robotics and Automation (ICRA), 2015 IEEE International Conference on IEEE (pp. 5010-5017)

Cao, H., Ling, Z., Zhu, J., Wang, Y., & Wang, W. (2009, December).  Design frame of a leg exoskeleton for load-carrying augmentation. In Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on (pp. 426-431). IEEE.

Lagoda, C., A wearable hand system for virtual reality. In Intelligent Robots and Systems      (IROS),       2017     

Shi, G., Wang, Y., & Li, S. (20150 Industrial Robot: An International Journal, 38(2), 163-171.

Field, M., Pan, Z., Stirling, D., & Naghdy, F. (2011). . (2016). Design Of      Control System For Articulated Robot Using Leap Motion Sensor.

Shi, G .(2015, May). Design and control of supernumerary robotic limbs for balance augmentation.

Cite This Work

To export a reference to this article please select a referencing stye below:

My Assignment Help. (2019). Gesture Recognition Leap Motion Controller And Exoskeleton Frame. Retrieved from https://myassignmenthelp.com/free-samples/gesture-recognition-leap-motion-controller.

"Gesture Recognition Leap Motion Controller And Exoskeleton Frame." My Assignment Help, 2019, https://myassignmenthelp.com/free-samples/gesture-recognition-leap-motion-controller.

My Assignment Help (2019) Gesture Recognition Leap Motion Controller And Exoskeleton Frame [Online]. Available from: https://myassignmenthelp.com/free-samples/gesture-recognition-leap-motion-controller
[Accessed 18 May 2024].

My Assignment Help. 'Gesture Recognition Leap Motion Controller And Exoskeleton Frame' (My Assignment Help, 2019) <https://myassignmenthelp.com/free-samples/gesture-recognition-leap-motion-controller> accessed 18 May 2024.

My Assignment Help. Gesture Recognition Leap Motion Controller And Exoskeleton Frame [Internet]. My Assignment Help. 2019 [cited 18 May 2024]. Available from: https://myassignmenthelp.com/free-samples/gesture-recognition-leap-motion-controller.

Get instant help from 5000+ experts for
question

Writing: Get your essay and assignment written from scratch by PhD expert

Rewriting: Paraphrase or rewrite your friend's essay with similar meaning at reduced cost

Editing: Proofread your work by experts and improve grade at Lowest cost

loader
250 words
Phone no. Missing!

Enter phone no. to receive critical updates and urgent messages !

Attach file

Error goes here

Files Missing!

Please upload all relevant files for quick & complete assistance.

Plagiarism checker
Verify originality of an essay
essay
Generate unique essays in a jiffy
Plagiarism checker
Cite sources with ease
support
Whatsapp
callback
sales
sales chat
Whatsapp
callback
sales chat
close