RPi Action Camera

Why?

ROS Nodes

The final demo consisted of 5 ROS nodes, each performing a particular task.

• Player Controller:
• Camera Node 1: takes in an image of the game board and outputs in current state and a reference location(A0).
• Camera Node 2: takes in an image of the pieces tray and outputs the location of the next piece to pick up.
• Robot Strategy/AI: takes in the current state of the board and outputs the coordinates for the next move.
• UR5e Movement Controller:

Overview

Fig 1: The circles/ellipses indicate the environment/sensor data/input data and rectangle with rounded edges indicate ROS nodes. The type of the ROS messages passed between the nodes is also shown.

Vision

For the simulation, there were 2 cameras that were set up - 1 located above the game board(camera 1) and another over the tray containing the pieces(camera 2).

Strategy/AI¹

The robot simply used a MinMax based strategy to play.

Fig 2: The strategy node represents the board as an array of ints to keep track of its state. It then runs the MinMax Algorithm to a depth of ?? and suggests the next move(represented by the triangle character).

Performance and Testing

Simplifications Made for Simulation

Due to limitations of time, several simplifications were made to the simulation to keep the environment as steady as possible². The idea was that once a simplified version of the simulation worked satisfactorily, the simplifications could be removed incrementally. Some of these are discussed below.

• Assets such as the tray and game board were made stationery(i.e. were omitted from the dynamics simulation). In addition, game pieces that were not being moved or about to be moved soon were made stationary(only on the game board) as the placement accuracy needed to be measured reliably. The primary reason for this was due to a limitation in the implementation of the e-pick in simulation³.

• Due to the e-pick limitation(mentioned above), the game pieces on the tray had to be spaced out significantly reducing the amount that could be placed on the tray from what was planned iniitially.

Fig 3: Original spacing(left), final spacing(right).

• Game piece tray simplified
• Collision shape of game pieces

Placement Accuracy

Footnotes

1. No, there’s nothing too fancy here. ↩

2. Considering the entire course spanned only 10 weeks, with only about 7~8 weeks to actually do the project, ↩

3. ↩