Revision as of 01:13, 21 March 2020

Project Team Members

Maximilian Apodaca - Computer Engineering

Daniel (Wei Te) Ha - Mechanical Engineering

Kaifan Yue - Mechanical Engineering

Project Overview

We set out to build a robot that can find its way to the user in a safe an reliable manor. In particular we were hoping to follow predefined GPS paths and avoid people along the way.

The project started by exploring two separate problems, detecting people and following a GPS path. Luckily for us the GPS path following had a rudimentary solution produced by the NotKiwiBot team. For the person detection we found a helpful tutorial online.

With these two problems solved we went about trying to integrate a new RTK GPS and the vision tracking into NotKiwiBot's code. A first draft of this was easier than expected as we only had to take control of the path planner when we saw a person.

After the first test integration we modified NotKiwiBot's path planner to run at a fixed speed (vs a fixed throttle) and applied some changes to decrease the wobble the car experiences while driving.

Main Components

Schematic

We have almost a standard schematic with the inclusion of the RTK GPS.

Hardware

Lasercut parts

3D Printed Parts
- Camera Mount and Protection Case

Our team designed camera mount that can easily adjust height and angle. During our use, the camera mount perfectly satisfied our need to finding best camera position for track training and later people detection.

We also tailor-made a protection case for the camera unit. It fits perfectly and can protect the whole unit as well as the lenses. The drawing is attached below.

- Camera Mount and Protection Case

The RTK GPS unit that we purchased is very expensive and powerful and we want to avoid any damage to it so that future teams can use it. You can download can print the case here:GPS Case and GPS Base

Drivetrain and Chassis

GPS RTK

Software

Github

All the software is on Github https://github.com/Pumuckl007/ECE148Car

RTK GPS

The RTK GPS works in a similar manor to a regular GPS. We communicate with it via a serial port and pass the standard NMEA messages. However it has additional functionality to handle RTCM data. RTCM is a way to send location correction data to the GPS. We implemented a client to handle (an NTRIP Client) this but did not end up using it.

As a result the code to read from the GPS amounts to opening a serial port with PySerial and parsing the NMEA with PyNema2. This has been documented with all the past GPS teams.

It is important to note that the RTK GPS we are using (C099-f9p) has a built in IMU to give high resolution movement data. That is to say it gives very high resolution movements but without RTK turned on can be up to a meter off in absolute position.

Path Following

The path following we used is very simple and almost identical to NotKiwiBot's implementation. Pick a look-ahead point and try and drive towards it. We do this by trying to match the direction of our car's motion to the direction to the point. This is illustrated in the figure below.

Each time we get close to the look-ahead point, which is within 5 meters in our case, we move the look-ahead point along the path we are trying to follow. This keeps the car targeting a point close enough to make a difference. The code for this can be found in the planner.py file.

Bearing From GPS

In order to find the bearing of the car we need to sample GPS data. However at low speeds this can be very noisy. As a result we take the centroids of the last two sets of two GPS coordinates and use that to extract heading information. For instance if we had the points [(1,1.8),(2,2.2),(3,2.2),(4,1.8)] we would compute the averages of the first two and last two points to get (1.5,2) and (3.5,2) and see that we are heading due west. If we just took that last two points (1,1.8),(2,2.2) we would assume we are heading south west.

Milestones

Future Work

Enable RTK to remove 1 meter absolute error
Handle people that are further away (right now there is a 4 meter limit)
Add sensor to stop before hitting a curb
Adapt speed based on turning radius
PID Controller for Steering to prevent wobble
Tune GPS Update Rate
Extrapolate position based on velocity to increase angle accuracy

@@ Line 76: / Line 76: @@
 = Future Work =
+* Enable RTK to remove 1 meter absolute error
+* Handle people that are further away (right now there is a 4 meter limit)
+* Add sensor to stop before hitting a curb
+* Adapt speed based on turning radius
+* PID Controller for Steering to prevent wobble
+* Tune GPS Update Rate
+* Extrapolate position based on velocity to increase angle accuracy

Difference between revisions of "2020WinterTeam1"

Revision as of 01:13, 21 March 2020

Contents

Project Team Members

Project Overview