Minimum Sensing Strategy for Path Planning and Path Following for an Autonomous Robot

2022 Fiscal Year Final Research Report

• Project/Area Number: 21K20425
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 0302:Electrical and electronic engineering and related fields
• Research Institution: Tokyo Institute of Technology
• Principal Investigator: Funada Riku 東京工業大学, 工学院, 助教 (50844247)
• Project Period (FY): 2021-08-30 – 2023-03-31
• Keywords: 制御 / 計測 / 経路計画 / 経路追従 / 移動ロボット

Outline of Final Research Achievements

The objective of this research project is to develop the minimum sensing strategy for a path planning and path following task, where the sensing effort of the robot is minimized to save the computational burden and energy. For this goal, we first quantify a sensing effort by a novel information-theoretic cost, where the amount of information acquired by the sensor is employed. Then, a path planning and path following method minimizing the designed sensing cost is developed. Second, we integrate the sensor model of the robot into the above path planning and path following method. The proposed method can present how the robot should adjust its sensor's specifications, such as the resolution and sensing frequency. Finally, we conducted simulation studies to verify the effectiveness of the proposed methods.

Free Research Field

制御

Academic Significance and Societal Importance of the Research Achievements

物流・保守点検といった分野で移動ロボットの活用が進む中，環境中を自律的に移動可能なシステムが求められている．この実現には，ロボットが自律的に環境を認識することが必要不可欠だが，環境認識に伴う計算量は膨大となる．本研究では，環境に対してあえて不注意になることを許容した経路計画・追従制御手法を構築することによって，計測に伴うコストを削減しつつ目的地への移動が可能となるシステムの構築を進めた．また，学術的にも，計測コストの削減を情報量の削減という新たな視点から数学的に厳密な形で表現しており，独自性が高いといえる．