Every year the field of robotics grows more complex and innovative as machines grow closer to being able to fully emulate human movement, function, and even expression. With growing knowledge in human physiology as well as advancements in human-machine interaction (HMI) the Electrical and Computer Engineering design team of Martin Kendal Ackerman, Jon Rose, Leyna Rasmussen, and Taskin Aydin focused on refining and implementing designs such as voice recognition, organic movements, and graphic human-machine interfacing. These exciting new technologies were implemented in a prototype humanoid torso with arms capable of hyper redundant movement.
If the degrees of freedom (DOF) of a robot are greater than the number of constraints imposed, the robot is then said to be redundant. If the robot has many redundant DOF’s, then the robot is said to be hyper-redundant. A hyper-redundant robot is thus more capable of mimicking the movements of a human. The TCNJ’s team’s robot has a total number of 10 DOF with 5 DOF in each arm. The number
of constraints imposed for each arm is 3. This allows both arms to move along an x, y, and even z axis. Additionally the robot was given an interactive face displayed as a 2D graphical medium on a computer screen. This face is capable of simulating human speech and can show human facial expressions in an organic fashion. The robot can interact with users through verbal communications using
a friendly animated human face and body language.
This project helps demonstrate how robots can be designed with a high level of intelligence that integrates both human like fluidity of movement and human-machine interaction. The project also investigates the technologies that will be required for furthering HMI projects in the future. “Humanoid interactive robots are attractive to us for their balanced utilization between robotics and artificial intelligence (AI). Engineering students involved in such projects gain cutting-edge knowledge on these improved AI techniques,” explains, robotics expert and faculty team advisor Dr. Jennifer Wang.
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