Difference between revisions of "2010 Practice Kick-off"

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(Output)
(Output)
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==Output==
 
==Output==
:Key learnings from game simulation
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===Key learnings from game simulation===
 
:* The single largest factor determining which alliance wins a match is which alliance wins autonomous.  The winner of autonomous goes immediately onto defense, whereas the looser goes onto offense.  If the loosing robots empty their hoppers during the autonomous period, they are in a position where they must first collect balls or return to the alliance wall to have their hoppers filled.  The defending autonomous winners are in a good position to refill hoppers (the BACKBOT from the field floor and the defending bots are already in proximity to their alliance wall).  The autonomous winners will therefore be in a better position to score during their offensive period.
 
:* The single largest factor determining which alliance wins a match is which alliance wins autonomous.  The winner of autonomous goes immediately onto defense, whereas the looser goes onto offense.  If the loosing robots empty their hoppers during the autonomous period, they are in a position where they must first collect balls or return to the alliance wall to have their hoppers filled.  The defending autonomous winners are in a good position to refill hoppers (the BACKBOT from the field floor and the defending bots are already in proximity to their alliance wall).  The autonomous winners will therefore be in a better position to score during their offensive period.
 
:* The BACKBOT needs to be able to pick balls off the field and have good storage capability.
 
:* The BACKBOT needs to be able to pick balls off the field and have good storage capability.
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:* Pivot bots work well at evading tank bots.
 
:* Pivot bots work well at evading tank bots.
  
:Strategy Statement
+
===Strategy Statement===
 
:* Dump & Shoot (not very realistic)
 
:* Dump & Shoot (not very realistic)
 
:* Pivot drive for agility & pushing capability
 
:* Pivot drive for agility & pushing capability
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:* As large a hopper as posssible
 
:* As large a hopper as posssible
 
:* Score a lot of points in autonomous
 
:* Score a lot of points in autonomous
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 +
===Specifications (game-centric)===
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:* Drive
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::* 10 ft/s max speed
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::* Same agility as [[DEWBOT VI]]
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:* Shooter
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::* 12 m/s max velocity
 +
::* Mount high on robot
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::* Camera fixed on shooter axis
 +
::* Aim the robot, not the shooter
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::* high rate of fire - 2/s
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::* Fixed elevation
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::* Wheel runs prior to shooting
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::* Run Lift<sub>2</sub> to shoot
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:* Lift<sub>2</sub>
  
 
==Feedback==
 
==Feedback==

Revision as of 01:34, 15 December 2010

In order to prepare for the 2011 Kick-off and to gain some experience and feedback from a new, more formal design process we intend to adopt, Team 1640 conducted a Practice Kick-off and front-end design excercise at the Downingtown Robotics Center on 11 & 12 December.

The Game

The 2006 FRC game, Aim High, was selected for this exercise. This game predates almost everyone's direct experience on 1640 (and is therefore a "new" game for almost all). Game documents were obtained from FIRST archives.
The 2006 game was modified only to incorporate current electronics and control elements. The cRIO was the controller. Electronics correspond to 2010 rules & components. For all other aspects, however, the 2006 rules applied.
A worksheet of Motor Curves was developed as a guide.

The Design Process

The design process piloted was based on the process introduced in Chapter 4 (and fleshed out in subsequent chapters) of Nigel Cross's "Engineering Design Methods, Strategies for Product Design - Fourth Edition" WILEY (2008). This is an undergraduate design textbook I picked up at the RPI bookstore on my last visit. A good read.
A front-end design process is proposed based on Cross's teachings and other sources more FIRST specific. This is a work-in-progress. Comments from all sources are more than welcome.
A dossier of Robot Profiles was built game simulation. These were assigned to students and used.

Output

Key learnings from game simulation

  • The single largest factor determining which alliance wins a match is which alliance wins autonomous. The winner of autonomous goes immediately onto defense, whereas the looser goes onto offense. If the loosing robots empty their hoppers during the autonomous period, they are in a position where they must first collect balls or return to the alliance wall to have their hoppers filled. The defending autonomous winners are in a good position to refill hoppers (the BACKBOT from the field floor and the defending bots are already in proximity to their alliance wall). The autonomous winners will therefore be in a better position to score during their offensive period.
  • The BACKBOT needs to be able to pick balls off the field and have good storage capability.
  • Gathering balls from the field is a good strategy.
  • Pivot bots work well at evading tank bots.

Strategy Statement

  • Dump & Shoot (not very realistic)
  • Pivot drive for agility & pushing capability
  • Ramp capable
  • Switchable autonomous - by position & tactics
  • Pick balls off floor (top load too is practical)
  • As large a hopper as posssible
  • Score a lot of points in autonomous

Specifications (game-centric)

  • Drive
  • Shooter
  • 12 m/s max velocity
  • Mount high on robot
  • Camera fixed on shooter axis
  • Aim the robot, not the shooter
  • high rate of fire - 2/s
  • Fixed elevation
  • Wheel runs prior to shooting
  • Run Lift2 to shoot
  • Lift2

Feedback

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