Robotic vision implementation
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Robotic vision implementation

Project period

06/27/2020 - 06/30/2020

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Robotic vision implementation
Robotic vision implementation

Deep learning is considered as an essential topic in fields like pattern recognition, machine learning, and computer vision. Few industrial robots are not human, they are machines. In addition, they can be programmed again, which means, the robot’s action can be modified by changing the control settings without replacing the hardware. They add some characteristics of traditional machines likewise as characteristics of machine operators. For an operator, it is easy to be taught to do a new task. But, for a machine, a task can be repeated for prolonged times with great precision.

An independent vision-based robot is usually considered to be intelligent robots that observe visual data, process it, and provide the required output. These robots are totally independent and don’t need any kind of human intervention since they are prefaced with instructions. A robot is usually designed on Raspberry Pi using OpenCV. This is used for object detection based on various properties. Here only a single object is being detected at a time. The tracking of the object is based on the division of the image into virtual grids. The movement of the robot is based on the position of the object in the grid. An arm is incorporated to pick the object once it is stationary. After picking the object, it would be dropped into its respective colored container which has a predefined position. Research shows that this algorithm has practical uses in a  vast number of areas, like face recognition, object tracking, and the position of an active vision sensor in real-life situations.

Why: Problem statement

Despite the attempts and the research work by the robot researchers to emulate human intelligence and appearance, the result is not achieved. Most robots still cannot see and are not a versatile object that is not properly recognized by it. For the effective and proper mechanism of robotics technology, it is important to prioritize the inefficiency associated with it. Though the wide use of robotics technology will take away many jobs of human beings and it will create unemployment in the society. The use of robots in performing various jobs will lead to the reduction of jobs of the human being so the initiation should be done systematically. The developments of robots will lessen many high-end precision jobs and will help in various sectors like more, but we focused on industrial purposes. This will lead to robots as a helper in the workplace with some degree of balance between the actual requirement and greed. The society should support and care for the developments in robotics technology as this will be beneficial for the people and the various sectors of an economy. Many tasks that are beyond human ability can be performed with the help of robotics and robotics in the war will be very helpful in its operation. The advancement of robot technology will be amazing and today, robots can be seen virtually in all the fields from transport to health, and recreations to industries. The use of this technology will get proclamations from society for taking away the jobs of an ordinary man. But to unravel the problems associated with this the usage of robots should be applied to chosen tasks and mostly be utilized in the areas where humans cannot reach or are not capable of performing.

How: Solution description

Robotic vision may be a good device for many automaton platforms. By creating robots perform adverse tasks, engineers nowadays square measure operating towards the eternal goal of transfer robots nearer to human life. One such task is the recognition or authentication of someone that is crucial in each social and industrial domains. Upon finding a face, the face recognition automaton either acknowledges it to be one from the information or just in case of a brand new person, adds it to the information. Indeed, there square measure variety of existing algorithms that are wont to deliver the goods this goal. For vision-based autonomous robots within the dynamic domain, it's crucial that the process algorithms square measure quickly additionally to being strong. This paper compares the potency of 3 algorithms - Eigenfaces, Fisherfaces, and native Binary Patterns Histograms. It conjointly compares the implementation of those algorithms on a Raspberry Pi against that on a computer. Empirical results demonstrating the robotic platform playing face recognition beneath varied circumstances, justify the validity of the planned style of a face recognition automaton.

 

How is it different from competition

We square measure proposing associate AI-powered robotic arm that's sometimes designed on Raspberry Pi mistreatment OpenCV and for sleuthing the user inputs and locates the article coordinate. when selecting the article, it'd be born into its various colored instrumentality that incorporates a predefined position. The gradual decreasing worth of hardware and also the rise of constructing new technologies is permitting designers to require advantage of state of the art tools in AI and laptop vision for a fraction of the worth. stress is given on preciseness vision-based robotic applications. Image acquisition by the mechanism is achieved by employing a PC-based digital camera, then it's sent to the image process computer code for any process. It will simply be perceived that the next generation of assembly technology can embrace versatile mechanism vision systems with a high level of skillfulness and lustiness.

 

Who are your customers

 

All industrialists, business individuals, and developers:

This is the foremost reason why an elementary step-change to simplifying the programming and mechanical quality of robotic steering applications is very important. Associate in Nursing innovative vision theme is simply 0.5 the battle. Mechanical reliableness additionally plays a vital role. This provides large advantages for business individuals. Implementation of machine vision in assembly and control processes is also a multilayer downside and demands so skilled information, experiences, innovations, and most often a problem-specific answer. Usually, the procedure of the planning Associate in Nursing development of a method of an assembly, examination and measure instrumentation victimization machine vision is split into the precise determination of tasks and goals like detection, recognition, grasping, handling, measure, fault detection, etc. and into machine vision part choice and dealing conditions determination like camera, computer, lenses, and optics, illumination, position determination, etc., With relevance the automatic assembly half handling, robotic handling, and assembly systems supply smart prospects for the rationalization and flexibilization of assembly and control processes

 

Project Phases and Schedule

  • Phase 1: putting in the Arm.

  • Phase 2: etymologizing Forward and Inverse mechanics equations for 6DOF.

  • Phase 3. Object Detection and applying the inverse mechanic's equations in Python cryptography.

  • Phase 4: Through serial communication, transferring the info.

  • Phase 5: Testing in the period.

  • These parts would possibly embrace end-of-arm tools (grippers, attachment torches, sprucing head, etc.) and sensors (such as force-torque sensors, safety sensors, vision systems, etc.). You’ll need to install the automaton on your producing floor by bolting it to a durable surface. Installation could boot involve adding part-feeding mechanisms, safeguards like protecting fencing, and more.

  • The robotic cell doesn’t solely embrace hardware. The controller comes with some pre-installed software system, however, you'll have to jot down the program—namely, the list of directions the automaton can follow to perform a specific task.

  • 1. the {planning|the look} part includes all of the tasks required to maneuver from the manual (or original) method to possess the plan and materials for the robotic cell.

  • From there, the integrated part consists of golf shot the items of the robotic cell along, programming it, and putting in the cell on the production line.

  • The operating part represents the highest goal of deployment: A productive robotic cell that will its job properly on Associate in Nursing current basis

Resources Required

Hardwares:

Robotic Arm with half-dozen Degrees of Freedom: Support wireless handle and free Android/iOS APP. offer graphical computer code. All employing a high-precision digital servo, that makes management additional correct. offer careful video tutorials to be told the way to use autoimmune disorder Arm. offer a 3D video to indicate you the way to assemble the robotic arm thoroughly. All-Metal Construction: Metal Mechanical Claw + metal Bracket + Metal Larger Bottom Plate. 6DOF structural style will create the robotic arm move flexibly, thus it will grab objects in any direction

Raspberry Pi module B+: The CM3+ calculate Module contains the middle of a Raspberry Pi three Model B+ (the BCM2837 processor ANd 1GB RAM) conjointly as an elective eMMC Flash device of 8GB, 16GB or 32GB (which is that the equivalent of the American state card at intervals the Pi)

 

Camera: find the Camera Module port. Gently pull au fait the sides of the port’s plastic clip. Insert the Camera Module ribbon cable, make sure the cable is that the proper approach is spherical. Push the plastic clip back to the place

Startup your Raspberry Pi. visit the foremost menu and open the Raspberry Pi Configuration tool. choose the Interfaces tab and make sure that the camera is enabled. bring up your Raspberry Pi.

Softwares:
  1. Python IDE

  2. Jupyter Notebook

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