Pioneering Near-Zero Latency Tele-Existence with Future Prediction Technology

2023 Fiscal Year Final Research Report

• Project/Area Number: 21H03409
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 60040:Computer system-related
• Research Institution: Kyoto University
• Principal Investigator: Awano Hiromitsu 京都大学, 情報学研究科, 准教授 (10799448)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: 知能ロボット / 推論の不確実性 / 模倣学習

Outline of Final Research Achievements

To enhance the usability of remote-controlled robots, a system was engineered that employs machine learning to anticipate sensory data and operator intentions. The system adjusts the strength of the guidance it provides to the user dynamically, based on the AI’s level of “confidence” in its predictions, thus ensuring the guidance feels natural and does not obstruct the user’s actions. The system is composed of an upper-body humanoid robot, a force-sensing device, and a neural network trained to mimic human actions. Experimental results demonstrated that by incorporating uncertainty into the guidance, the time taken to fold a towel could be reduced by 16.2%.

Free Research Field

知能ロボット

Academic Significance and Societal Importance of the Research Achievements

学術的意義：AIの推論結果に対する"自信"に応じて人に提示する操作ガイダンスの強度を動的に変化させる枠組みを構築・有効性を実証したこと。
社会的意義：遠隔操作ロボットが必要とされる多くの分野において、その操作性・効率性改善に向けた方策を示したこと。また柔軟物操作というロボットにとってはチャレンジングなタスクでタスク遂行時間を有意に削減できることを実証したこと。