《智能机器人技术》教学大纲
课程代码 | 045101671 |
课程名称 | 智能机器人技术 |
英文名称 | Intelligent Robotics |
课程类别 | 选修课 |
课程性质 | 选修 |
学时 | 总学时：48上机学时：0实验学时：12实践学时：0 |
学分 | 2.5 |
开课学期 | 8 |
开课单位 | 计算机科学与工程学院 |
适用专业 | 计算机科学与技术、软件技术、网络工程、自动控制、机械电子 |
授课语言 | 中文 |
先修课程 | |
毕业要求（专业培养能力） | 本课程对学生达到如下毕业要求有如下贡献： 1.研究：能够基于科学原理并采用科学方法对与计算机相关复杂工程问题进行研究，包括设计实验、分析与解释数据、并通过信息综合得到合理有效的结论。 2.使用现代工具：能够针对与计算机相关复杂工程问题，开发、选择与使用恰当的技术、资源、现代工程工具和信息技术工具，包括对复杂工程问题的预测与模拟，并能够理解其局限性。 3.工程与社会：能够基于工程相关背景知识进行合理分析，评价计算机专业工程实践和复杂计算机工程问题解决方案对社会、健康、安全、法律以及文化的影响，并理解应承担的责任。 4.环境和可持续发展：能够理解和评价针对与计算机相关复杂工程问题的专业工程实践对环境、社会可持续发展的影响。 |
课程培养学生的能力（教学目标） | 通过本课程的教学，使学生了解移动机器人系统的软硬件组成、运动学分析、传感器、感知、定位、作图，以及机器人的基本控制体系结构等基本知识。培养学生对人工智能技术的兴趣，认识机器人对社会进步与经济发展的作用；培养学生综合运用所学基础理论和专业知识进行创新设计的能力。 |
课程简介 | 智能机器人技术是一门跨多个学科的综合性技术，它涉及计算机、自动控制、传感器、人工智能、电子技术和机械工程等多种学科的内容。由于机器人学涉及的内容较多，本课程以移动机器人为主进行讲授。 |
教学内容与学时分配 | 1、理论教学部分： （一）课程思政授课（1学时） 教学内容：实现计算机专业知识教学与立德树人教育的有机融合；结合 “人工智能”、 “智能制造”等国家战略，激发学生的爱国情怀和“实干兴邦”的爱国奋斗精神。 智能机器人导论（3学时） 教学内容：了解移动机器人学研究的目的、研究对象、主要类型等，以及移动机器人学在国内外发展现状。 教学要求：初步了解移动机器人学在国内外发展现状。 （二）运动（4学时） 教学内容：讲解移动机器人运动方式，运动类型，运动的关键问题。重点讲解腿式移动机器人和轮式移动机器人的主要运动方式及机构。 教学要求：掌握移动机器人主要运动形式和主要机构。 重点：掌握轮式移动机器人的主要运动方式及机构。 难点：运动机构的运动方式和原理。 （三）移动机器人运动学（6学时） 教学内容：讲解移动机器人位置描述、运动学模型建立，移动机器人运动学约束，以及移动机器人基本的运动控制。 教学要求：掌握移动机器人位置描述、运动学模型、运动学约束，并了解移动机器人基本的运动控制算法。 重点：掌握移动机器人位置描述、运动学模型、运动学约束。 难点：运动学模型的建立和运动学约束分析。 （四）感知（6学时） 教学内容：讲解移动机器人应用的主要传感器类型，基本原理，主要技术指标，及其应用特点和应用方式。 教学要求：了解移动机器人应用的主要传感器类型，基本原理，主要特点和应用方式。 重点：掌握编码器、超声波传感器、GPS、陀螺、摄像机等主要传感器的特点和原理，以及特征数据提取的初步方法。 难点：传感数据的不确定性和特征数据的提取。 （五）移动机器人的定位（6学时） 教学内容：主要讲解影响移动机器人精确定位的主要误差源素，误差模型的建立，信任度的表示，地图表示法，基于概率地图的定位，以及其他定位方式。 教学要求：掌握分析影响移动机器人精确定位的方法、误差模型、地图表示法、基于概率地图的定位 重点：掌握误差模型建立、地图表示法、基于概率地图的马尔科夫定位 难点：误差模型、马尔科夫定位 （六）规划与导航（6学时） 教学内容：主要讲解移动机器人路径规划的基本原理和方法，以及如何实现壁障技术和壁障算法。最后介绍导航控制的体系结构。 教学要求：掌握移动机器人路径规划的基本原理和方法，以及移动机器人控制的基本体系结构。 重点：移动机器人路径规划的基本原理和方法，以及移动机器人导航控制的基本体系结构。 难点：移动机器人碰撞检测技术和避碰算法。 （七）课堂报告和参观（4学时） 学生参观实验室和在课堂上分组展示课程实验报告。 |
实验教学（包括上机学时、实验学时、实践学时） | 有（实验学时：12） |
教学方法 | 课堂讲授、课程设计 |
考核方式 | 创新型实验+课题研究报告 占该课程总评成绩的 100 %。 |
教材、实验指导书及教学参考书目 | [1]R.西格沃特、I.R. 诺巴克什 著. 自主移动机器人导论. 李人厚译，西安交通大学出版社 [2]Saeed B.Niku. 机器人学导论. 孙富春等译，电子工业出版社 [3]Mitchell，机器学习. 曾华军等译，机械工业出版社 |
制定人及制定时间 | 李方 2019年5月 |
“Intelligent Robotics” Syllabus
Course Code | 045101671 |
Course Title | Intelligent Robotics |
Course Category | Specialty-related Course |
Course Nature | Elective Course |
Class Hours | Class Hours: 48 Lab Hours: 12 |
Credits | 2.5 |
Semester | 8 |
Institute | The School of Computer Science and Engineering |
ProgramOriented | Computer Science and Technology, Software Technology, Network Engineering, Automatic control, Machinery and Electronics |
Teaching Language | Chinese |
Prerequisites | |
Student Outcomes (Special Training Ability) | 1.Research: An ability to conduct investigations of complex engineering problems based on scientific theories and adopting scientific methods including design of experiments, analysis and interpretation of data and synthesis of information to provide valid conclusions. 2.Applying Modern Tools: An ability to create, select and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering activities, with an understanding of the limitations. 3.Engineering and Society: An ability to apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice. 4.Environment and Sustainable Development: An ability to understand and evaluate the impact of professional engineering solutions in environmental and societal contexts and demonstrate knowledge of and need for sustainable development. |
Teaching Objectives | Through the teaching of this course, students can understand the basic knowledge of the hardware and software composition, kinematics analysis, sensor, perception, positioning, mapping and basic control architecture of mobile robot system. Cultivating students' interest in artificial intelligence technology. Make students understand the role of robots in social progress and economic development. And cultivating students' ability for innovatively design via basic theory and professional knowledge. |
Course Description | Intelligent robot technology is a comprehensive technology across multiple disciplines. It involves the computer, automatic control, sensors, artificial intelligence, electronic technology and mechanical engineering and other disciplines. As the robotics involved much content, this course is focused on mobile robot. |
Teaching Content and Class Hours Distribution | Theory teaching part: （A）Courses in ideological and political education (1 hour) (B) Introduction to Intelligent Robot (3 hours) Teaching content: understand the purpose of mobile robotics research, research object, the main type, as well as mobile robotics at home and abroad development status quo. Teaching requirements: a preliminary understanding of mobile robotics at home and abroad development status quo. (C) Motion (4 hours) Teaching content: explain the mobile robot motion, motion type and the key issues of motion. Focusing on the motion and mechanisms of leg mobile robots and wheeled mobile robots. Teaching requirements: master the main form of motion and main mechanisms of mobile robots. Focus: master the main motion and mechanisms of wheeled mobile robots. Difficulties: the motion type and principles of motive mechanisms. (D) Mobile robot kinematics (6 hours) Teaching content: explain the description of mobile robot position, establishment of kinematic model, mobile robot kinematic constraints and mobile robot basic motion control. Teaching requirements: master the mobile robot position description, kinematic model, kinematic constraints and understand the basic motion control algorithm of mobile robots. Focus: master the mobile robot position description, kinematic model and kinematic constraints. Difficulty: the establishment of kinematic model and analysis of kinematic constraint. (E) Perception (6 hours) Teaching content: explain the main sensor types, basic principles, main technical indexes, application characteristics and application methods of mobile robot applications. Teaching requirements: understand the main sensor types, basic principles, main features and application methods of mobile robot applications. Focus: master the characteristics and principle of encoder, ultrasonic sensor, GPS, gyro, camera and other main sensors, as well as the initial method of feature data extraction. Difficulties: the uncertainty of sensing data and the extraction of characteristic data. (F) Localization of mobile robot (6 hours) Teaching content: mainly on the influence of the main error sources for precise positioning of the mobile robot, the error model is established, expressing trust, map representation, probabilistic map positioning, positioning and other ways. Teaching requirements: master the method of analysis, accurate localization of mobile robot, error model, map representation and location based on probability map. Focus: Mastering error model building, map representation and Markoff mapping based on probability map. Difficulties: error model and Markoff localization. (G) Planning and navigation (6 hours) Teaching content: the basic principles and methods of mobile robot path planning, and how to implement barrier technology and barrier algorithm are discussed. Finally, the architecture of navigation control is introduced. Teaching requirements: master the basic principles and methods of mobile robot path planning, and the basic architecture of mobile robot control system. Difficulties: collision detection and collision avoidance algorithms for mobile robots. (H) Classroom reports and visits (6 hours) Students visit the laboratory and display experimental reports in groups in class. |
Experimental Teaching | 12 Hours |
Teaching Method | Classroom teaching, Innovative experiment |
Examination Method | Innovative experiment + Research report |
Teaching Materials and Reference Books | [1] Roland Siegwart. Introduction to Autonomous Mobile Robots. MIT Press MA [2] Saeed B.Niku. Introduction to Robotics. John Wiley Sons [3] Mitchell. Machine Learning. McGraw Hill Education |
Prepared by Whom and When |
《智能机器人技术》实验教学大纲
课程代码 | 145030 |
课程名称 | 智能机器人技术 |
英文名称 | Intelligent Robotics |
课程类别 | 选修课 |
课程性质 | 选修 |
学时 | 总学时：48 实验：12 实习：0 其他：0 |
学分 | 2.5 |
开课学期 | 8 |
开课单位 | 计算机科学与工程学院 |
适用专业 | 计算机科学与技术、软件技术、网络工程、自动控制、机械电子 |
授课语言 | 中文 |
先修课程 | |
毕业要求（专业培养能力） | 本课程对学生达到如下毕业要求有如下贡献： 1.研究：能够基于科学原理并采用科学方法对与计算机相关复杂工程问题进行研究，包括设计实验、分析与解释数据、并通过信息综合得到合理有效的结论。 2.使用现代工具：能够针对与计算机相关复杂工程问题，开发、选择与使用恰当的技术、资源、现代工程工具和信息技术工具，包括对复杂工程问题的预测与模拟，并能够理解其局限性。 3.工程与社会：能够基于工程相关背景知识进行合理分析，评价计算机专业工程实践和复杂计算机工程问题解决方案对社会、健康、安全、法律以及文化的影响，并理解应承担的责任。 4.环境和可持续发展：能够理解和评价针对与计算机相关复杂工程问题的专业工程实践对环境、社会可持续发展的影响。 |
课程培养学生的能力（教学目标） | 通过本课程的教学，使学生了解移动机器人系统的软硬件组成、运动学分析、传感器、感知、定位、作图，以及机器人的基本控制体系结构等基本知识。培养学生对人工智能技术的兴趣，认识机器人对社会进步与经济发展的作用；培养学生综合运用所学基础理论和专业知识进行创新设计的能力。 |
课程简介 | 智能机器人技术是一门跨多个学科的综合性技术，它涉及计算机、自动控制、传感器、人工智能、电子技术和机械工程等多种学科的内容。由于机器人学涉及的内容较多，本课程以移动机器人为主进行讲授。 |
主要仪器设备与软件 | 计算机，移动机器人 |
实验报告 | |
考核方式 | 实验为设计性实验，占课程成绩的50%。实验成绩从四个方面进行评估：创意（30%）、技术难度（40%）、实验结果（10%）、实验报告（20%）。 |
教材、实验指导书及教学参考书目 | [1]R.西格沃特、I.R. 诺巴克什 著. 自主移动机器人导论. 李人厚译，西安交通大学出版社 [2]Saeed B.Niku. 机器人学导论. 孙富春等译，电子工业出版社 [3]Mitchell，机器学习. 曾华军等译，机械工业出版社 |
制定人及发布时间 | 李方 2019年5月 |
《智能机器人技术》实验教学内容与学时分配
实验项目编号 | 实验项目名称 | 实验学时 | 实验内容提要 | 实验类型 | 实验要求 | 每组人数 | 主要仪器设备与软件 |
01 | 机器人避障 | 12 | 在机器人软件平台上建立一个包含若干个静止障碍物和运动障碍物的仿真环境，设定机器人的起始点和终点后，机器人能够规划出一条从起始点到目标点的安全路径。查阅相关路径规划算法，实现一种以上算法并相互比较。要求给出源代码、试验结果并且进行演示。 | 设计性 | 选做 | 2-3人 | 计算机 |
02 | 多机器人围捕 | 12 | 在机器人软件平台上建立一个包含若干个静止障碍物的仿真环境，环境中还包括一个随机运动的目标和四个机器人，四个机器人要对运动目标进行围捕，如果运动目标被机器人围在中心，或者被围靠在墙角，则机器人成功围捕了目标。查阅相关机器人协作算法，实现一种以上算法并相互比较。要求给出源代码、试验结果并且进行演示。 | 设计性 | 选做 | 2-3人 | 计算机 |
03 | 机器人足球 | 12 | 在机器人足球仿真平台上编写足球机器人的智能决策程序，能进行多机器人对抗赛。要求给出源代码、试验结果并且进行演示。 | 设计性 | 选做 | 2-3人 | 计算机 |
04 | 机器人视觉 | 12 | 使用摄像头捕捉图像，编写图像识别算法，对运动的物体（如红色的物体或球体）等进行跟踪。要求给出源代码、试验结果并且进行演示。 | 设计性 | 选做 | 2-3人 | 计算机 |
05 | 机器人运动 | 12 | 在开发环境中编写相应的代码并烧录进机器人开发板中，完成红外循线测试、超声波测试、电机测试、颜色传感器测试。要求给出源代码、试验结果并且进行演示。 | 设计性 | 选做 | 2-3人 | 移动机器人 |
06 | 机器人智能搬运 | 12 | 在开发环境中编写相应的代码并烧录进机器人开发板中，完成在给定的场地中将不同颜色的圆柱块搬运到指定位置。要求给出源代码、试验结果并且进行演示。 | 设计性 | 选做 | 2-3人 | 移动机器人 |
07 | 自选项目 | 12 | 自行设计（经过教师审核同意）。针对机器人的某方面关键技术即应用，查阅相关资料；设计和实现算法；给出源码、测试结果及结论。 | 设计性 | 选做 | 2-3人 | 移动机器人 |
“Intelligent Robotics” Syllabus
Course Code | 145030 |
Course Title | Intelligent Robotics |
Course Category | Elective Courses |
Course Nature | Elective Course |
Class Hours | 12 |
Credits | 2.5 |
Semester | 8 |
Institute | The School of Computer Science and Engineering |
Program Oriented | Computer Science and Technology, Software Technology, Network Engineering, Automatic control, Machinery and Electronics |
Teaching Language | Chinese |
Prerequisites | |
Student Outcomes (Special Training Ability) | 1.Research: An ability to conduct investigations of complex engineering problems based on scientific theories and adopting scientific methods including design of experiments, analysis and interpretation of data and synthesis of information to provide valid conclusions. 2.Applying Modern Tools: An ability to create, select and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering activities, with an understanding of the limitations. 3.Engineering and Society: An ability to apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice. 4.Environment and Sustainable Development: An ability to understand and evaluate the impact of professional engineering solutions in environmental and societal contexts and demonstrate knowledge of and need for sustainable development. |
Teaching Objectives | Through the teaching of this course, students can understand the basic knowledge of the hardware and software composition, kinematics analysis, sensor, perception, positioning, mapping and basic control architecture of mobile robot system. Cultivating students' interest in artificial intelligence technology. Make students understand the role of robots in social progress and economic development. And cultivating students' ability for innovatively design via basic theory and professional knowledge. |
Course Description | Intelligent robot technology is a comprehensive technology across multiple disciplines. It involves the computer, automatic control, sensors, artificial intelligence, electronic technology and mechanical engineering and other disciplines. As the robotics involved much content, this course is focused on mobile robot. |
Instruments and Equipments | Computer,Mobile robots |
Experiment Report | |
Assessment | The experiment is a design experiment, accounting for 50% of the course results. The experimental results were evaluated from four aspects: creativity (30%), technical difficulty (40%), experimental results (10%), and experimental reports (20%). |
Teaching Materials and Reference Books | [1] Roland Siegwart. Introduction to Autonomous Mobile Robots. MIT Press MA [2] Saeed B.Niku. Introduction to Robotics. John Wiley Sons [3] Mitchell. Machine Learning. McGraw Hill Education |
Prepared by Whom and When |
“CourseTitle” Experimental Teaching Arrangements
No. | Experiment Item | Class Hours | Content Summary | Category | Requirements | Number of StudentsEach Group | Instruments, Equipments and Software |
| 1 | Robot obstacle avoidance | 12 | The robot is able to plan a safe path from the starting point to the target point by setting up a simulation environment that includes several static obstacles and movement obstacles on the robot software platform. After setting the starting point and end point of the robot, Access to the relevant path planning algorithm to achieve more than one algorithm and compare with each other. Request to give the source code, test results and demonstrate. | Design | Compulsory | 2-3 people | Computer |
| 2 | Multi-robot roundabout | 12 | In the robot software platform to establish a simulation environment containing a number of static obstacles, the environment also includes a random movement of the target and four robots, four robots to round the target of the movement, if the moving target by the robot around the center, Or be encircled in the corner, the robot successfully hijacked the target. Access to the relevant robot collaboration algorithm to achieve more than one algorithm and compare with each other. Request to give the source code, test results and demonstrate. | Design | Elective | 2-3 people | Computer |
| 3 | Robot Soccer | 12 | In the robot soccer simulation platform to write soccer robot intelligent decision-making process, can carry out multi-robot race. Request to give the source code, test results and demonstrate. | Design | Elective | 2-3 people | Computer |
| 4 | Robot vision | 12 | Use the camera to capture images, write image recognition algorithm, the movement of objects (such as red objects or spheres) and so on to track. Request to give the source code, test results and demonstrate. | Design | Elective | 2-3 people | Computer |
| 5 | Robot movement | 12 | In the development environment to write the appropriate code and burn into the robot development board, complete the infrared line test, ultrasonic testing, motor testing, color sensor testing. Request to give the source code, test results and demonstrate. | Design | Elective | 2-3 people | Mobile robots |
| 6 | Robot intelligent handling | 12 | In the development environment to write the appropriate code and burn into the robot development board, completed in a given site will be different colors of the cylinder block to the specified location. Request to give the source code, test results and demonstrate. | Design | Elective | 2-3 people | Mobile robots |
| 7 | Optional items | 12 | Self - designed (with the teacher 's approval). For the robot some aspects of the key technology that is applied, access to relevant information; design and implementation of the algorithm; given the source code, test results and conclusions. | Design | Elective | 2-3 people | Computer |
