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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/robotic-mapping-trajectory-generation
课程评论：没有评论
课程名称：机器人地图绘制与轨迹生成 课程概述：在这门“机器人地图绘制与轨迹生成”的课程中，学员将学习如何使用反馈控制方法执行（非）完整运动系统的基本逆向运动学。同时，学员将掌握如何处理多维传感器信号，如激光测距仪，以进行地图绘制。此外，课程将重点讨论机制和传感器作为不确定性的来源，并教授如何对其进行建模和控制的技术。 课程大纲： 1. 高级传感器：测距仪和齐次变换 - 描述：在课程的第一周，您将了解“测距仪”设备这一类，它们在地图绘制中有着重要的应用，同时还将学习齐次变换以执行坐标变换。 2. 地图绘制：基本表示方法 - 描述：在这一周，您将开始理解基本的离散地图表示及其实现方式。 3. 地图绘制：概率表示和配置空间 - 描述：本周将介绍简单的方式来以概率形式编码障碍物，配置空间的概念，以及一个简单的碰撞检测算法。 4. 逆向运动学：轨迹跟随 - 描述：在这一周，您将学习如何基于一系列航点定义机器人轨迹，并在Webots中实现基本的比例控制器，以在二维环境中导航。 5. 实施地图绘制与轨迹生成 - 描述：在这个模块中，您将把您的地图绘制和轨迹跟随技能转移到一个商业机器人平台上，介绍在真实机器人平台上传感器集成的额外约束。 通过本课程的学习，您将能够掌握机器人在复杂环境中移动和绘制地图的基本技能，为后续的机器人技术奠定坚实的基础。
Name:Advanced Sensor: Range finders and Homogeneous transforms
Description:Welcome to Robotic Mapping and Trajectory Generation. In this first week of the course, you will get started by being introduced to the class of "range finder" devices, which have important applications in mapping, as well as the concept of homogeneous transforms to perform coordinate transformations.
Name:Mapping: Basic Representations
Description:In this week, you will begin to understand basic discrete map representations and their implementation.
Name:Mapping: Probabilistic Representations and Configuration Space
Description:This week introduces simple ways to encode obstacles in terms of probability, the concept of "configuration space", and a simple algorithm for collision checking.
Name:Inverse Kinematics: Trajectory Following
Description:In this week you will learn to define a robot trajectory based on a series of waypoints and implement a basic proportional controller in Webots to navigate in a 2D environment.
Name:Implementing Mapping and Trajectory Generation
Description:In this module you will transfer your mapping and trajectory following skills to a commercial robotic platform in a kitchen environment, introducing you to additional constraints of sensor integration on a real robotic platform.
In this second course of the Introduction to Robotics specialization, "Robotic Mapping and Trajectory Generation", you will learn how to perform basic inverse kinematics of (non-)holonomic systems using a feedback control approach. You will also learn how to process multi-dimensional sensor signals such as laser range scanners for mapping. Additionally, you will apply the overarching focus of mechanisms and sensors as sources of uncertainty and gain techniques to how to model and control them.
