This repository will be used for Solving Inverse Kinematics for the robotic arm at ACME Robotics. It is currently used for only manipulators having six degree of freedom. The input coordinates [X,Y,Z] are send as an input to the IK solver to get the output_joint_angles. We have created the FK solver in order to check for robot arm constraints are in the bias range or not. We use FK_solver in order to check for the output_bias and to cancel out singularities of the robot arm.
This software will compute the trajectory when you input your desired location which will return a vector of all the joint angles for the robot. We simulate our tracjectory using matplotlib for all the output coordinates covered till the desired location.
This IK solver can be integrated with any six degree of robot manipulator. A robotic manipulator is used to direct material without direct physical contact with the operator. It was developed to handle hazardous materials or access places that are not easily accessible by humans. At Acme, the manipulator will be used for picking heavy containers from the conveyer belt of the production line and placing it on the packaging line. The manipulator will have four degrees of freedom and will be placed on a support structure, between the production and packaging line conveyor belts.
We are considering Stanford Arm for our IK solver algorithm.
The main applications of this software is to solve the inverse kinematics of the robot manipulator given the end effector coordinates.
We are developing an inverse kinematics solver for 6 DOF serial Manipulators at ACME robotics.
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When equipped with a 3D Camera it can be used as a Vision-Guided Inspection Robot.
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The 3D camera is being used for identification and detection of an object in an assembly line.
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The output pose from the camera is given as an input to the Robot which will calculate the joint angles using IK solver and place the object in the desired location set by the user.
-This robot can be used for random part inspection in an assembly line.
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UML diagrams representing the contracts.
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C++11 and C++14 and implemented the code using best software practices.
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Continous Integration (Travis Badges) for reporting the build phase over changes.
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It can be integrated with a vision to give a real time vision guidance process in a manufacturing process.
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It can be used for various applications such as Error Proofing,Palletizing and Depalletizing,Real time guidance and bin picking.
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These manipulators can be used for multiple parts.
We have simulated our output using visual-Kinematics(matplotlib).
We have created two solvers methods , FK solver which will calculate the forward kinematics of the robot given the input_joint_angles.
We Use Denavit-Hartenberg representation for solving Inverse Kinematics.
IK Solver which will calculate the joint angles based upon the end effector coordinates.
For the simulation we take all the joint angle coordinates returned by the IK solver are visualized through the matplotlib.
Created a test suite to check for all the methods.
We followed Test Driven Approach - Pair Programmning and completed the process using Agile Iterative Process.
The software design includes three blocks namely kinematics, simulation, and testing. Incremental Rotary encoders will be used at each motor link to calculate the angle moved by a particular arm.
- Kinematics This block consists of two sections, Inverse Kinematics and Forward Kinematics.
2.Simulation Matplotlib will be used for the simulation.
3.Testing Software testing will be done to check the repeatability, effectiveness of the output.
Unit tests will be performed to check the values of encoders and the working of specific functions.
We have created unit tests to check the output_bias as to adhere to the safety constraints of the robot manipulator.
UID:118172507
Master's Student at University of Maryland,College Park
UID:118191058
Master's Student at University of Maryland,College Park
Badges for Travis and Coveralls are located at the top of the readme file. Additional information on building the software to test for coverage is shown below.
sudo apt-get install lcov
cmake -D COVERAGE=ON -D CMAKE_BUILD_TYPE=Debug ../
make
make code_coverage
Running the above code will generate a index.html page. Check the build/coverage folder and view it in a web browser.
We are going with a BSD 3-Clause License.
Please find the below google docs for the Product backlog and sprint planning sheets.
To check Project Quadchart: https://drive.google.com/file/d/1f5DGQsuPYc3aL75Bu-q06wnC6IMKLkDA/view?usp=sharing
To check Phase-2 update presentation video: https://drive.google.com/file/d/1AXTdUfsSIRdeRG1VYXJFTEf1PN5SPOOi/view?usp=sharing
To check Project Backlog (Product Backlog, Iteration Backlogs, and Work Log): https://docs.google.com/spreadsheets/d/1uzkHEVrKEj08UWGMlCNrI8JZQGKhPk-L/edit#gid=1646452053
To check Sprint Planning Notes/Review:
https://docs.google.com/document/d/1zEVBw1UfMGHF_3bLddfBvVKr5AerR_yLoXSyQXR5pro/edit?usp=sharing
We have two dependancies for the software to function properly.
- Eigen : We use this package for all our kiematics calculations.
- Visual Kinematics(Matplotlib) : It is used for Showing our IK solver methods
- Python 2.7 or 3.8
While running the main source code , we are getting segementation core dumped due to issues with the eigen package. Need to resolve in the next iteration.
Having issue while installing matplotlib.
Added to the backlog for the next iteration.
The issue where the source file might have issue is when the dependancies are not installed properly.
Make sure you install the correct packages.
Check out this link for installing Eigen: https://eigen.tuxfamily.org/dox/GettingStarted.html
Check out this link for installing matplotlib: https://matplotlib-cpp.readthedocs.io/en/latest/
Check out this link for visual kinematics - python https://github.com/dbddqy/visual_kinematics
sudo apt-get install git
git clone --recursive https://github.com/ameyakonk/ENPM808X_Midterm_Manipulator_IKSolver.git
cd <path to repository>
git checkout remotes/origin/Phase1
mkdir build
cd build
cmake ..
make
Run program: ./app/shell-app
To Run the demo: cd .. && python3 demo.py
Run tests: ./test/cpp-test
sudo apt-install doxywizard
run doxywizard
source it to ENPM808X_Midterm_Manipulator_IKSolver/
run the doxygen
check your destination folder for the doxygen docs. --> Check doxygen folder for the doxygen documentation
BSD 3-Clause License.
Copyright (c) 2021, ACME Robotics, Rahul Karanam , Ameya Konkar All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.