Human Tactile Gesture Interpretation for Robotic Systems

Abstract-- Human-robot interactions are less efficient and communicative than human-to-human interactions, and a key reason is a lack of informed sense of touch in robotic systems. Existing literature demonstrates robot success in executing handovers with humans, albeit with substantial reliance on external sensing or with primitive signal processing methods, deficient compared to the rich set of information humans can detect. Simply grasping an object with acceptable grip forces A. Motivation and Applications Some examples of HRI handovers require the human to apply An ultimate goal of the robotics sector of Human-Robot aggressive forces for the robot to detect when to release a Interaction (HRI) is to enable interactions so natural and transferred object [10], and others implement thresholding of efficient as to reach parity with human-human interactions. A different approach that Attainment of this lofty goal can be significantly advanced results in markedly "humanlike" HRI handovers requires a by improving a robotic system's keen sense of touch, a sense fixed, calibrated external camera [12], a reliance that cannot which humans seamlessly and continuously use to perform be feasibly implemented on mobile platforms or in dynamic any physical task. The incorporation of machine learning tools to assist robotic systems with interpreting contact with their environments There are many works in the existing literature that make has led to more sophisticated improvements.