Difference between revisions of "2020WinterTeam7"
(→Design and Assembly of Donkey) |
(→Jetson Nano case) |
||
| Line 58: | Line 58: | ||
=== Jetson Nano case === | === Jetson Nano case === | ||
To house our Jetson Nano, we 3D printed a case taken off of Thingiverse at: | To house our Jetson Nano, we 3D printed a case taken off of Thingiverse at: | ||
| − | |||
https://www.thingiverse.com/thing:3518410 | https://www.thingiverse.com/thing:3518410 | ||
| + | [[File:Jetson_Case.jpg|400px]] | ||
== Autonomous Driving using gradient descent== | == Autonomous Driving using gradient descent== | ||
Revision as of 12:38, 20 March 2020
Contents
Project Overview
Our goal was to provide our car with particular GPS coordinates, have the car navigate to the destination coordinates by using GPS and RTK2 corrections to achieve centimeter accuracy. We utilized Potential Functions and Gradient descent algorithm to avoid obstacles and find the path through objects.
Main objectives of adaptive cruise control are:
1. GPS-RTK Navigation from source to the assigned destination
2. Connecting the two C099-F9P GPS-RTK2 modules using Odin (wifi)
3. Obstacle avoidance
Team Members
Chanyang Yim – Mechanical and Aerospace Engineering Department
Jiuqi Wang – Mechanical and Aerospace Engineering Department
Omid Hasanli – Electrical and Computer Engineering Department
Design and Assembly of Donkey
Camera Mount, GPS Case, and Antenna Base Design
This part includes all the CAD files during the project.
Camera Mount
The camera mount contains three parts, the purpose of this design is to let the camera be adjustable with height and angle. The first part is the camera base, which mounts the camera with four bolts and nuts, and can be mounted on the upper stand with one bolt. The second part is the upper stand, this part has many holes on it to make sure the camera can adjust the height. The last part is the stand, the holes mate the holes on the upper stand.
In our design, the first camera mount was not perfect, the camera did not have enough angles to adjust, and the stand was very thin. Therefore, here shows the modified design of our camera mount.
GPS Case
The GPS we used is a bare circuit board, which needs protection. A GPS case was designed to protect the GPS from bumps. GPS case contains two parts, GPS cover and GPS base.
Antenna Base
Similar to GPS, there was an antenna base to make sure the antenna was stable during operation.
Jetson Nano case
To house our Jetson Nano, we 3D printed a case taken off of Thingiverse at:
https://www.thingiverse.com/thing:3518410
Autonomous Driving using gradient descent
The General Idea
To build potential fields, so that the point that represents the robot is attracted by the goal and repelled by the obstacle region. The robot moves to a lower energy configuration and energy is minimized by following the negative gradient of the potential energy function.
Artificial Potential Field Methods
The Attractive Potential
– Uatt is the “attractive” potential --- move to the goal
The Repulsive Potential
– Urep is the “repulsive” potential --- avoid obstacles
Total Potential Function
– Uatt is the “attractive” potential --- move to the goal
– Urep is the “repulsive” potential --- avoid obstacles
Gradient Descent
Final Result
Challenges
Conclusion
Our car is capable of correcting its direction to move towards a specified GPS location using RTK2 corrections from base GPS-RTK within 1-10cm and avoiding larger objects. From our demo, we can see that the system is not robust enough to fully navigate to multiple locations while avoiding objects.
Project Links
Resources
- Robotic Motion Planning: http://www.cs.cmu.edu/~motionplanning/lecture/Chap4-Potential-Field_howie.pdf
- Autonomous and Mobile Robotics: https://www.dis.uniroma1.it/~oriolo/amr/slides/MotionPlanning3_Slides.pdf
