Project Team: Matthew Ferrara<\/p>\n\n\n\n
Advisor: Dr. Seung-yun Kim<\/p>\n\n\n\n
Using TCNJs research robot\nBaxter, the project uses computer vision to recognize checkers pieces,\ncalculate their relative position in 3D space, and allow Baxter to pick\/place\nthe piece. This functionality will be integrated with an open-source algorithm\nfor the board game checkers, with the goal of enabling Baxter to play the game\nwithout any human intervention besides initial startup.<\/p>\n\n\n\n
The project uses image\nrecognition libraries to extract useful information (features) from Baxter\u2019s\nhead and hand cameras. These features with then be transformed into 3D\ncoordinates relative to Baxter\u2019s position. From there, inverse kinematic (IK)\nequations will be used to position Baxter\u2019s joints to properly pick\/place the\nidentified piece.<\/p>\n","protected":false},"excerpt":{"rendered":"
Project Team: Matthew Ferrara Advisor: Dr. Seung-yun Kim Using TCNJs research robot Baxter, the project uses computer vision to recognize checkers pieces, calculate their relative position in 3D space, and allow Baxter to pick\/place the piece. This functionality will be integrated with an open-source algorithm for the board game checkers, with the goal of enabling … Continue reading Game Piece Recognition using Baxter Robot<\/span>