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Miniature of Robot Detection Using Gradient and Color Signatures
Robot Detection Using Gradient and Color Signatures

Date: 2016-05-01

Creator: Megan Marie Maher

Access: Open access

Tasks which are simple for a human can be some of the most challenging for a robot. Finding and classifying objects in an image is a complex computer vision problem that computer scientists are constantly working to solve. In the context of the RoboCup Standard Platform League (SPL) Competition, in which humanoid robots are programmed to autonomously play soccer, identifying other robots on the field is an example of this difficult computer vision problem. Without obstacle detection in RoboCup, the robotic soccer players are unable to smoothly move around the field and can be penalized for walking into another robot. This project aims to use gradient and color signatures to identify robots in an image as a novel approach to visual robot detection. The method, "Fastgrad", is presented and analyzed in the context of the Bowdoin College Northern Bites codebase and then compared to other common methods of robot detection in RoboCup SPL.
Miniature of RoboGrams: A lightweight message passing architecture for RoboCup soccer
RoboGrams: A lightweight message passing architecture for RoboCup soccer

Date: 2015-01-01

Creator: Elizabeth Mamantov, William Silver, William Dawson, Eric Chown

Access: Open access

RoboGrams is a lightweight and efficient message passing architecture that we designed for the RoboCup domain and that has been successfully used by the Northern Bites SPL team. This unique architecture provides a framework for separating code into strongly decoupled modules, which are combined into configurable dataflow graphs. We present several different architecture types and preexisting message passing implementations, but among all of these, we contend that Robo-Grams' features make it particularly well suited for use in RoboCup. As a success story, we describe the Northern Bites' use of RoboGrams and the benefits it has provided to a single team, but we also suggest that it could help SPL teams collaborate in the future.