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最終更新日：2026年10月16日
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最終更新日：2026年10月16日
授業計画や教室は変更となる可能性があるため、必ずUTASで最新の情報を確認して下さい。
UTASにアクセスできない方は、担当教員または部局教務へお問い合わせ下さい。
Biologically Inspired Robotics
Biologically Inspired Robotics
This course introduces the principles of biologically inspired robotics and embodied intelligence. Students will learn how biological systems use body morphology, materials, sensing, control, learning, and interaction with the environment to generate adaptive behavior.
The course covers representative examples from animals, humans, and plants, and examines how biological principles can be translated into robotic systems. Students will also explore how modern AI and robotics can be combined with biological inspiration to design new machines.
By the end of the course, students should be able to:
- explain key principles of biologically inspired robotics;
- analyze biological systems from an engineering perspective;
- relate morphology, sensing, control, and environment to robot behavior;
- propose a biologically inspired robotic concept.
The course covers representative examples from animals, humans, and plants, and examines how biological principles can be translated into robotic systems. Students will also explore how modern AI and robotics can be combined with biological inspiration to design new machines.
By the end of the course, students should be able to:
- explain key principles of biologically inspired robotics;
- analyze biological systems from an engineering perspective;
- relate morphology, sensing, control, and environment to robot behavior;
- propose a biologically inspired robotic concept.
時間割／共通科目コード
コース名
教員
学期
時限
3729-105
GEN-PE5916L3
Biologically Inspired Robotics
飯田 史也
木曜3限
マイリストに追加
マイリストから削除
講義使用言語
英語
単位
2
実務経験のある教員による授業科目
NO
他学部履修
可
開講所属
工学系研究科
授業計画
The course will cover the following topics:
- Introduction: Why learn robotics from biology?
- Embodied intelligence and morphological computation
- Biological and bio-inspired robot locomotion
- Muscles, tendons, and compliant actuation
- Soft robotics and functional materials
- Biological sensing and active perception
- Sensing and perception
- Neural control, reflexes, and central pattern generators
- Learning, adaptation, and developmental robotics
- Collective behavior and distributed intelligence
- Evolution and evolutionary robotics
- Generative AI, embodied AI, and the future of biologically inspired robotics
- Student presentations and discussion
The detailed order may be adjusted according to class progress and student interests.
授業の方法
Classes combine lectures, discussion, case studies, and student activities.
Students will be encouraged to use generative AI as a learning and exploration tool—for example, to investigate biological systems, compare robotic approaches, develop questions, and explore new design ideas. The emphasis is on active learning rather than memorization.
成績評価方法
Assessment will be based on:
Class participation and short assignments: 30%
Final project/report: 40%
Final presentation: 30%
The final project will propose and analyze a biologically inspired robotic system or research idea.
履修上の注意
After class:
Students should review the main concepts and explore examples or literature related to topics that particularly interest them.
