工业机器人2.0时代来临 宾夕法尼亚大学机器人硕士专业未来可期!

　　近几年，机器人在工业上应用广泛，比如：汽车制造、3C电子制造、五金制造、陶瓷卫浴、物流运输……各个行业都运用了工业机器人来替代，工业机器人2.0时代已经来临，从而对机器人研发人才的需求量持续上涨，为了顺应时代的需求，宾夕法尼亚大学就开设了机器人硕士专业，下面，就随小编来看看吧，希望对大家有所帮助：

　　Master’s in Robotics

　　这个多学科项目由计算机和信息科学系、电气和系统工程系、机械工程和应用力学系联合发起。

　　由世界顶尖的机器人研究中心之一的GRASP实验室管理，教育学生在机器人、视觉、感知、控制、自动化和机器学习的科学和技术。

　　该课程旨在为学生提供全面的机器人背景，同时也提供足够的灵活性，让学生专注于更广泛的领域内的特定领域的研究。

　　课程设置：

　　Artificial Intelligence:

　　CIS 519 Applied Machine Learning

　　CIS 520 Machine Learning

　　CIS 521 Fundamentals of AI

　　ESE 650 Learning in Robotics

　　Robot Design and Analysis:

　　MEAM 510 Design of Mechatronic Systems

　　MEAM 520 Introduction to Robotics

　　MEAM 620 Advanced Robotics

　　Control:

　　ESE 500 Linear Systems

　　ESE 505/MEAM 513 Control Systems Design

　　MEAM 517 Control & Optimization w/Applications in Robotics

　　ESE 619 Model Predictive Control

　　Perception:

　　CIS 580 Machine Perception

　　CIS 581 Computer Vision & Computational Photography

　　CIS 680 Adv. Topics in Machine Perception

　　Technical Elective Courses (must complete at least 5)

　　BE 521 Brain-Computer Interfaces

　　BE 570 Biomechatronics

　　CIS 502 Analysis of Algorithms

　　CIS 510 Curves & Surfaces: Theory & Applications

　　CIS 511 Theory of Computation

　　CIS 515 Foundations of Linear Algebra & Optimization

　　CIS 519 Applied Machine Learning

　　CIS 520 Machine Learning

　　CIS 521 Fundamentals of AI

　　CIS 526 Machine Translation

　　CIS 530 Computational Linguistics

　　CIS 540 Principles of Embedded Computation

　　CIS 541 Embedded Software for Life-Critical Applications

　　CIS 545 Big Data Analytics

　　CIS 560 Computer Graphics

　　CIS 562 Computer Animation

　　CIS 563 Physically Based Animation

　　CIS 564 Game Design & Development

　　CIS 565 GPU Programming & Architecture

　　CIS 580 Machine Perception

　　CIS 581 Computer Vision & Computational Photography

　　CIS 610 Advanced Geometric Methods

　　CIS 620 Advanced Topics in AI

　　CIS 625 Computational Learning Theory

　　CIS 680 Adv. Topics in Machine Perception

　　CIS 700 Data-Driven Robotic Perception and Control (*other topics considered a general elective for ROBO)

　　CIS 700 Integrated Intelligence for Robotics (*other topics considered a general elective for ROBO)

　　CIS 700 Topics in Machine Perception (*other topics considered a general elective for ROBO)

　　ENM 510 Foundations of Engineering Math I

　　ENM 511 Foundations of Engineering Math II

　　ENM 520 Principles and Techniques of Applied Math I

　　ENM 521 Principles and Techniques of Applied Math II

　　ESE 500 Linear Systems

　　ESE 504 Introduction to Optimization

　　ESE 505/MEAM 513 Control Systems Design

　　ESE 512 Dynamical Systems for Engineering and Biological Applications

　　ESE 514 Graph Neural Networks

　　ESE 518 Learning for Dynamics

　　ESE 519 Real Time & Embedded Systems

　　ESE 530 Elements of Probability Theory & Random Processes

　　ESE 531 Digital Signal Processing

　　ESE 546 Principle of Deep Learning

　　ESE 547 Introduction to Legged Locomotion

　　ESE 601 Hybrid Systems

　　ESE 605 Convex Optimization

　　ESE 615 F1/10 Autonomous Racing

　　ESE 617 Nonlinear Systems

　　ESE 618 Learning for Dynamics and Control

　　ESE 619 Model Predictive Control

　　ESE 625 Nanorobotics

　　ESE 650 Learning in Robotics

　　ESE 680 Dynamic Programming (*other topics considered a general elective for ROBO)

　　ESE 680 Learning for Controls (*other topics considered a general elective for ROBO)

　　IPD 501 Integrated Computer-Aided Design, Manufacturing & Analysis

　　MEAM 508 Materials for Manufacturing

　　MEAM 510 Design of Mechatronic Systems

　　MEAM 513/ESE 505 Control Systems Design

　　MEAM 516 Advanced Mechatronic Reactive Spaces

　　MEAM 517 Control and Optimization with Applications in Robotics

　　MEAM 520 Introduction to Robotics

　　MEAM 535 Advanced Dynamics

　　MEAM 543 Performance and Design of Unmanned Aerial Vehicles (UAVs)

　　MEAM 545 Aerodynamics

　　MEAM 620 Robotics

　　MEAM 624 Distributed Robotics

　　MEAM 625 Haptic Interfaces – not currently being offered

　　PSYC 579 Experimental Methods in Perception

　　ROBO 599 (ESE/CIS/MEAM 599 for older students starting before Fall 2014) *Masters Independent Study (Note: Only one Independent Study may be taken for the degree)

　　ROBO 597 (ESE/CIS/MEAM 599 for students starting before Fall 2014) *Masters Thesis Research (Click here for masters thesis requirements.)

　　General Elective Courses (at most 2)

　　CIS 505 Software Systems

　　CIS 522 Deep Learning

　　CIS 523 Ethical Algorithm Design

　　CIS 548 Operating Systems Design and Implementation

　　CIS 550 Database & Info Systems

　　CIS 553 Networked Systems

　　CIS 700 Special Topic (not specifically listed on the technical electives courses page)

　　EAS 512 Engineering Negotiations

　　EAS 545 Engineering Entrepreneurship I

　　EAS 546 Engineering Entrepreneurship II

　　ENM 502 Numerical Methods & Modeling

　　ENM 503 Introduction to Probability & Statistics

　　ESE 540 Engineering Economics

　　ESE 543 Human Systems Engineering

　　ESE 545 Data Mining

　　ESE 680 Special Topic (not specifically listed on the technical electives courses page)

　　IPD 504/BE 514 Rehab Engineering and Design

　　IPD 511 Creative Thinking & Functional Iteration in Design

　　IPD 514 (MEAM514) Design for Manufacturability

　　IPD 515 Product Design (formerly MEAM 515)

　　IPD 525 Ergonomics/Human Factors Based Product Design

　　IPD 527 (ARCH727) Industrial Design I

　　PHIL 530 Philosophy of Artificial Intelligence

　　申请条件：

　　机器人专业理学硕士的申请人需要在计算机科学、电气工程或机械工程方面有较强的学术背景。

　　综上所述，以上讲的就是关于宾夕法尼亚大学机器人硕士专业的相关问题介绍，希望能给各位赴美留学的学子们指点迷津。近年来，赴美留学一直是广大学生最热门的话题，同时，很多学生对于签证的办理、院校的选择、就业的前景、学习的费用等诸多问题困扰不断，别担心，IDP留学专家可以为你排忧解难，同时，更多关于赴美留学的相关资讯在等着你，绝对让你“浏览”忘返。在此，衷心祝愿各位学子们能够顺利奔赴自己心目中理想的学校并且学业有成!