智慧系統之感知與決策
Perception and Decision Making in Intelligent Systems
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 智慧系統之感知與決策 EC329 2 節連堂 |
6 14:20–15:10 |
* 根據陽明交大上課時間表所列
Welcome to the Perception and Decision Making in Intelligent Systems! In recent years, we have witnessed tremendous progress in intelligent systems such as self-driving cars and robotics. We have witnessed significant progress in social media and demonstrations. Do you know how they realize these applications? Do you know how recent advances in artificial intelligent power these systems? What are the new challenges of applying AI to these intelligent systems? Please sign up for this course if interested in diving into this field! The intended learning outcomes of this course are: - Identify the key components of intelligent systems - Explain the key components of intelligent systems, i.e., robot navigation and robot manipulation systems - Apply key components to build robot navigation and manipulation systems - Explain the difference between conventional and recent data-driven intelligent systems - Deliver a scientific presentation - Develop your own solution for intelligent systems
Programming (C/C++/Python), Linear Algebra, Probability, Computer Vision, and Machine Learning
Course Assignment: 50% (4 or 5 computer assignments) - HW1: Robot Navigation - 3D Scene Reconstruction - HW2: Robot Navigation - 3D Semantic Mapping - HW3: Robot Navigation - Path Planning - HW4: Robot Manipulation - Grasping - HW5: Robot Manipulation - IK and FK Final Project (per group, 2-3 people a group): 35% - Participate in Embodied AI Challenges (https://embodied-ai.org/) - Present YOUR algorithm for solving one of the challenges by the end of the semester Paper Presentation: 15% Every group (2-3 people a group) will record a presentation of a paper. Each group will be assigned to watch another group's presentation and should ask questions. The final score depends on the quality of the presentation, the raised questions, and the response to the questions.
- Spatial Representation and Image Formation
- State Estimation
- Planning and Control
- Robot Navigation
- Robot Manipulation
- Intelligent Driving Systems
| 週次 | 主題 |
|---|---|
| 第 1 週 | |
| 第 2 週 | |
| 第 3 週 | |
| 第 4 週 | |
| 第 5 週 | |
| 第 6 週 | |
| 第 7 週 | |
| 第 8 週 | |
| 第 9 週 | |
| 第 10 週 | |
| 第 11 週 | |
| 第 12 週 | |
| 第 13 週 | |
| 第 14 週 | |
| 第 15 週 | |
| 第 16 週 |
Slides, papers, and online resources