Autonomous People Mover

ASEE Conference 2016

Joe Hudden, Cody Smith

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Team

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BackgroundRochester Institute of Technology is re-entering the field of autonomous vehicle research.

Research and development of autonomous vehicles are becoming more and more popular in the automotive industry. It is believed that autonomous vehicles are the future for easy and efficient transportation that will make for safer, less congested roadways.

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Problem Statement• Current State• There have been two phases of this project so far. The first phase focused on modifying a golf

cart into a remote controlled vehicles. The second phase tried to complete the of the first phase. Our phase did a ground-up re-design of all hardware software.

• Desired State• APM is capable of driving autonomously, including tasks such as localization, path planning,

path following, and object avoidance. APM provides a simple human-machine interface which displays diagnostic information. APM is able to be remote-controlled. Passengers have the ability to take manual control of the vehicle at any time.

• Project Goals• APM can drive autonomously on a closed course while avoiding static and moving obstacles,

staying on the designated path, and maintaining the safety of passengers and bystanders.

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Control Subsystems

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Brake• Linear actuator attached to cable on stock brake pedal

• Position control from 0-100% braking effort,PID implemented

• Engaged automatically by emergency stop

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Throttle• Analog signal sent to stock motor controller

• Adjustable mapping via software

• Amplified from microcontroller to match stock voltage

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• Utilizes electric power steeringrack from Wicked

• Converts single DAC output todifferential output to match stocktorque sensors

• Position control viapotentiometer with built insoftware limits

• PID control

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Steering

Full Controls Test Video

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Main PCB• Custom PCB for control subsystem circuits

• Connectors for interface with stock cart wiring loom

• Low-pass filtering for sensitive signals

• Power conversion

• Sounder and LED’s for status and error

• Expandable

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Sensors

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LiDAR• Velodyne Puck (VLP-16)• 16 channels

• ± 15° vertical FOV

• 360° horizontal FOV

• 100m range

• 300,000 points/second

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Ultrasonics• MB7363 HRXL-MaxSonar®-WRLS™• 1mm resolution

• Operates on 3.3 V

• Measures distance to objects

• Maximum range of 10 meters (394 inches)

• Sensor output: analog voltage

• Matches standard ¾-inch PVC pipe fittings for mounting

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IMU• MPU-9250 9-Axis Motion Tracker• 3 axis gyro

• Row, pitch, yaw

• 3 axis accelerometer

• X, Y, Z acceleration – full scale range from ± 2g to ± 16g

• 3 axis magnetometer

• Compass

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GPS• RTK compatible

• ± 10 cm accuracy with RTK lock

• Active antenna with ground plane

• Custom PCB

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Software

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Vehicle Simulation• Uses state-space equations for 3 DoF “bicycle” model

• Solution approximated in MATLAB using ode45 command

• Inputs:• Waypoints

• Forward velocity set point

• Initial conditions

• Vehicle properties

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Vehicle Simulation

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Lateral Distance from CG (ft)

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MicrocontrollersArduino DUE 1

• Throttle control

• Steering control

• Brake control

• RC input

• Encoder odometry

Arduino DUE 2

• Ultrasonics input

• IMU

• Light

• Sounder

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ROSdue• Serial communication between ROS and Arduino

• ROS node and Arduino library

• 115200 baud (adjustable)

• Publisher and subscriber interface

• 3-way handshake for subscribers

• Robust• Message length checksum

• Character range and type verification

• Auto-restart on failure

• Open source (http://github.com/codysmithd/ROSdue)

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Desktop PC (ROS)• Ubuntu 14.04

• ROS Indigo

• ROS Packages:• robot_navigation

• tf

• Hector SLAM

• Autonomous driving

• Touch-screen user interface

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Desktop Software Overview

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Remote Control Mode Video

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Come see our demo at

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Questions

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