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!
