e-Inu: 感情知能を持つ四足歩行ロボットのシミュレーション
e-Inu: Simulating A Quadruped Robot With Emotional Sentience
強化学習とソフトウェア工学を組み合わせ、人間の感情を認識し、歩容生成や音声・画面上の表情で応答する四足ロボットを仮想シミュレーションした研究。
著者: Abhiruph Chakravarty, Jatin Karthik Tripathy, Sibi Chakkaravarthy S, Aswani Kumar Cherukuri, S. Anitha, Firuz Kamalov, Annapurna Jonnalagadda
分類: cs.RO, cs.HC, cs.LG
原文アブストラクト
Quadruped robots are currently used in industrial robotics as mechanical aid to automate several routine tasks. However, presently, the usage of such a robot in a domestic setting is still very much a part of the research. This paper discusses the understanding and virtual simulation of such a robot capable of detecting and understanding human emotions, generating its gait, and responding via sounds and expression on a screen. To this end, we use a combination of reinforcement learning and software engineering concepts to simulate a quadruped robot that can understand emotions, navigate through various terrains and detect sound sources, and respond to emotions using audio-visual feedback. This paper aims to establish the framework of simulating a quadruped robot that is emotionally intelligent and can primarily respond to audio-visual stimuli using motor or audio response. The emotion detection from the speech was not as performant as ERANNs or Zeta Policy learning, still managing an accuracy of 63.5%. The video emotion detection system produced results that are almost at par with the state of the art, with an accuracy of 99.66%. Due to its "on-policy" learning process, the PPO algorithm was extremely rapid to learn, allowing the simulated dog to demonstrate a remarkably seamless gait across the different cadences and variations. This enabled the quadruped robot to respond to generated stimuli, allowing us to conclude that it functions as predicted and satisfies the aim of this work.