Challenges Difficulty Estimation

Challenge Difficulty Estimation

Content

1Challenges Brief Description 1

2Robot Characteristic 2

3Characteristic-Challenge Value 3

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Challenge Difficulty Estimation

The scope of this document is to assign an arbitrary value to the importance of various factors for the challenges of the Pi Wars to draw specifications and focus design effort

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1Challenges Brief Description

• A1 Lava Palaver: Autonomous drag race in a near straight line with a bump
  
• R1 Pi Noon: Two robots face off, each trying to pop the balloons of the other
  
• R2 Zombie Apocalypse: Fire balls and darts against targets in a multi story arena
  
• R3 Obstacle Course: The robot must clear a series of obstacles like ramps and traps
  
• AR1 Eco Disaster: Move green targets in blue area
  
• AR2 Escape Route: Navigate a Labyrinth the pilot can't see directly
  
• AR3 Mine Sweeper: 4x4 Simon Says
  

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2Robot Characteristic

• Clearance: Size of the obstacle that can be cleared. Ability to recover after disturbances.
  
• Precision: Error committed when trying to achieve given attitude/position
  
• Reaction Time: Latency. How quickly can the robot respond to events
  
• Speed: Maximum top speed that can be achieved
  
• Power: Pushing power of the robot. How quickly can the robot accelerate to top speed.
  
• Pilot/Auto-Pilot Skills: How good the pilot is. Outmanoeuvring skills. Decision making.

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3Characteristic-Challenge Value

I assign a value for each characteristic for each challenge based on how improving said characteristic would impact scoring in the challenge.
There are three values:

• +1: Improving this characteristic would give disproportionate advantage in this challenge
  Example: Increasing the top speed in a race would directly decrease clearance time and achieve direct score improvement
  
• +0: Improving this characteristic would yield results in this challenge proportional to the effort invested
  Example: Investing in precision would improve results in navigating a maze, but not disproportionately so.
  
• -1: Improving this characteristic would give little advantage in the challenge
  Example: Improving clearance in a a challenge that involves moving on a flat plane would achieve no improvements in the score