Banner Engineering Corp. (Minneapolis) partnered with a Minnesota West Community and Technical College engineering student and robotics instructor to develop a robot designed to play the Guitar Hero video game-responding to each note as it appears onscreen. Pete Nikrin, who graduated from Minnesota West in 2008 and now works as a manufacturing engineer at Meier Tool & Engineering, designed the robot to compete with a friend that Nikrin had introduced to the game and, after playing for two weeks, had surpassed Nikrin in his ability.
Bill Manor, robotics instructor at Minnesota West, suggested Nikrin incorporate a PresencePLUS P4 OMNI vision sensor with a right-angle lens from Banner Engineering. Manor had such a vision system in his possession, as Minnesota West had purchased it at a discount through Banner as a start-up education kit.
“Students have used Banner vision sensors in many projects over the years-to inspect containers, for example, as they come down a conveyor,” Manor says.
To develop his Guitar Hero robot, Nikrin used a mannequin-complete with Minnesota West sweatshirt, hat and painted fingernails-and installed the camera lens as the robot's left eye, which would be positioned toward the TV or computer screen. The robot, named Roxanne, identified the notes to be played by using an Edge vision tool, which detects, counts and locates the transition between bright and dark pixels in an image area.
“We set-up five Edge tools that ran horizontally across the screen, one for every fret, and positioned the tools to focus on the notes at the bottom of each,” Nikrin says. “The Edge tools sent a constant signal as the five vertical fret lines progressed, and when a bright white dot appeared in the middle of a dark colored circle, the Edge tool allowed the sensor detect it.”
Jeff Curtis, senior applications engineer at Banner, worked with Nikrin and Manor to ensure the robot's processing time was fast enough to keep up with the video game. Once a note was identified, communicating this signal efficiently depended upon a heavy amount of programming, as well as Ethernet technology applied through a Modbus register. A PLC was programmed so that it constantly looked at the vision sensor's register. Once the Edge tool senses a note, the PLC notices the change in the register, and the logic in the PLC fires a solenoid that activates the robot's finger. Just as a human player would react, the robot's finger then presses down on the appropriate note on the guitar. This set-up resulted in 9 ms processing speed.
“We honed a Locate tool and gave it a fixed point-a piece of reflective tape on the PC monitor-to focus on,” Curtis said. “This ensures the Edge tools are in the proper location to detect each note as it comes along and allows for any slight vibration in the application environment that could result in some deviation. If the robot starts to sag a bit, for example, it can still play.”
Using this technique, Roxanne has, on Medium mode, hit 100% accuracy at times, and it averaged 98% accuracy during the remainder of Nikrin's tenure at Minnesota West. She could achieve up to 95% accuracy on Hard mode and 80% accuracy on Expert mode, due to the increased mechanical requirements of the robot's fingers required. Today, Roxanne still engages current and prospective Minnesota West engineering students, and Nikrin looks back on it with both a sense of accomplishment and a hefty dose of gratitude.
“Throughout the process, I was impressed with Banner's dedication to their products and customers,” he adds. “Bill and I both thought that they went above and beyond to help with a school project, which might seem trivial to some companies.”
Banner Engineering manufactures fiber optic assemblies, photoelectric and ultrasonic sensors, vision sensors, wireless networks, electronic machine guarding systems and precision measurement systems. View a video ofRoxanne's performance.
Banner Engineering Corp.