Course Description 课程简介
Introduces the fundamental algorithmic approaches for creating robot systems that can autonomously manipulate physical objects in unstructured environments such as homes and restaurants. Topics include perception (including approaches based on deep learning and approaches based on 3D geometry), planning (robot kinematics and trajectory generation, collision-free motion planning, task-and-motion planning, and planning under uncertainty), as well as dynamics and control (both model-based and learning-based).
介绍创建机器人系统的基本算法方法，该系统可以在家庭和餐馆等非结构化环境中自主操纵物理对象。主题包括感知（包括基于深度学习的方法和基于 3D 几何的方法）、规划（机器人运动学和轨迹生成、无碰撞运动规划、任务和运动规划以及不确定性下的规划）以及动力学和控制（基于模型和基于学习）。
Homework assignments will guide students through building a software stack that will enable a robotic arm to autonomously manipulation objects in cluttered scenes (like a kitchen). A final project will allow students to dig deeper into a specific aspect of their choosing. The class has hardware available for ambitious final projects, but will also make heavy use of simulation using cloud resources.
家庭作业将指导学生构建一个软件堆栈，使机械臂能够在杂乱的场景（如厨房）中自主操作物体。最终项目将允许学生更深入地研究他们选择的特定方面。该课程拥有可用于雄心勃勃的最终项目的硬件，但也将大量使用云资源进行模拟。
6.4210 is the undergraduate version of the class. It serves as an Advanced Undergraduate subject (AUS), Independent Inqu