Digitizing Human Motion via Bending Sensors toward Humanoid Robot

Abstract

A humanoid robot is an advanced representation of robot techniques. It can move like a human and possesses the ability to use human tools. Sensing and intelligent control technologies have increased the intelligence of humanoid robots. However, the dexterity of a humanoid robot is still far from that of a human. Herein, a bending sensor is introduced to detect human motion, which can thus be digitized to enable a humanoid robot to learn to be more dexterous. This bending sensor is fabricated of carbon fiber with a cascade structure, resulting in excellent characteristics, including a quantitative detection capability, high gauge factor, low hysteresis, long‐term durability, and high‐frequency response. Thus, the bending sensor can recognize both the large‐scale motion of joint bending and subtle motion of muscle contraction. Fourteen bending sensors corresponding to the 14 knuckles of the human hand can accurately recognize and digitize hand gestures. These multichannel sensors are combined with nine additional bending sensors to comprehensively digitize the grasping process of the upper limb and recognize the grasping of objects with different sizes and weights. These successful applications demonstrate that the bending sensor can open a path toward learning human behavior for a humanoid robot.

Keywords

• bending sensors
• gesture recognition
• grasping process digitization
• human motion digitization
• humanoid robots