Autonomous navigation vehicle algorithms

Introduction

A great resource is F1Tenth, https://f1tenth.org/

See also https://mushr.io/tutorials/tuning/ and https://racecar.mit.edu/platform

Safety Concerns

• Real-life problems
• Sensors
• Failure modes

Automatic breaking AEB

Automatic emergency breaking AEB

• Detect objects
• Find range, velocity, heading
• Determine critical objects. Time to collision TTC.

• False positive: Nobody will buy a system with these
• False negative: kills innocent people

Stop the vehicle before colliding.

Sensors

• Camera
  • Structured light 3d scanner camera
  • Stereo camera
  • Monocular camera
• Radar
• Ultrasonic
• Lidar
  • Planar lidar (Hokuyo 30LX)
  • 3d lidar
  • solid state lidar (Velodyne velarray)
• Odometry

Reactive Methods

Follow the Gap A (naive method)

Follow the gap

Furthest distance?

• Misreading
• Too small gap

Gap: Series of at least $n$ consecutive hits that pass some distance threshold $R$.

Labs from F1tenth

1. Wall following https://f1tenth-coursekit.readthedocs.io/en/latest/assignments/labs/lab3.html#doc-lab3

More references

• Quaternions: Steven M. LaValle - Virtual reality lectures https://www.youtube.com/playlist?list=PL_ezWOhnpakMojiJGm-YiCz5zr4GpuLG_
• Names of the coordinates: https://www.ros.org/reps/rep-0105.html
• Ziegler-Nichols method for PID https://en.wikipedia.org/wiki/Ziegler%E2%80%93Nichols_method
• Harmonic potential field path planning for high speed vehicles https://folk.ntnu.no/skoge/prost/proceedings/acc08/data/papers/0383.pdf
• Robotic Motion Planning: Potential Functions https://www.cs.cmu.edu/~motionplanning/lecture/Chap4-Potential-Field_howie.pdf