Efficiency of algorithms, orders of magnitude, recurrence relations, lower-bound techniques, time and space resources, NP-complete problems, polynomial hierarchies, and approximation algorithms. Sorting, searching, set manipulation, graph theory, ... matrix multiplication, fast Fourier transform, pattern matching, and integer and polynomial arithmetic.

Study of algorithms from the distributed and concurrent systems literature. Formal approach to specifying, verifying, and deriving such algorithms. Areas selected from mutual exclusion, resource allocation, quiescence detection, election, Byzantine ... agreements, routing, network protocols, and fault-tolerence. Formal approaches will handle system specification and verification of safety, liveness, and real-time properties.

Automated planning of actions to accomplish some desired goals. Basic algorithms, important systems, and new directions in the field of artificial intelligence planning systems.

Input, output, and storage of pictorial information. Pictures as information sources, efficient encoding, sampling, quantization, approximation. Position-invariant operations on pictures, digital and optical implementations, the pax language, ... applications to matched and spatial frequency filtering. Picture quality, image enhancement and image restoration. Picture properties and pictorial pattern recognition. Processing of complex pictures; figure extraction, properties of figures. Data structures for pictures description and manipulation; picture languages. Graphics systems for alphanumeric and other symbols, line drawings of two- and three-dimensional objects, cartoons and movies.

Information visualization defined in relation to graphics, scientific visualization, databases, data mining, and human-computer interaction. Visualizations for dimensional, temporal, hierarchical and network data. Examines design alternatives, ... algorithms and data structures, coordinated views, and human factors evaluations of efficacy.

Methods for unconstrained and constrained minimization of functions of several variables. Sensitivity analysis for systems of algebraic equations, eigenvalue problems, and systems of ordinary differential equations. Methods for transformation ... of an optimization problem into a sequence of approximate problems. Optimum design sensitivity analysis.
Restriction: Permission of ENGR-Aerospace Engineering department.

Analysis techniques for manipulator kinematics and dynamics. DH parameters, serial and parallel manipulators, approaches to redundancy. Applications of robots to space operations, including manipulators on free-flying bases, satellite servicing, ... and planetary surface mobility. Sensors, actuators, and mechanism design. Command and control with humans in the loop.

Engineering requirements supporting humans in space. Life support design: radiation effects and mitigation strategies; requirements for atmosphere; water, food, and temperature control. Accommodations for human productivity in space: physical ... and psychological requirements; work station design; and safety implication of system architectures. Design and operations for extra-vehicular activity.

General Mechanical
This is an introductory graduate level course in critical thinking about formal methods for design in mechanical engineering. Course participants gain background in these methods and the creative potential each offers to designers. Participants ... will formulate, present, and discuss their own opinions on the value and appropriate use of design materials for mechanical engineering.
Prerequisites: Graduate standing or permission of instructor.

General Mechanical
Modern control theory for both continuous and discrete systems. State space representation is reviewed and the concepts of controllability and observability are discussed. Design methods of deterministic observers are presented and optimal ... control theory is formulated. Control techniques for modifying system characteristics are discussed.
Prerequisite: ENME462; or permission of instructor.

In the course of engineering design, project management, and other functions, engineers have to make decisions, almost always under time and budget constraints. Managing risk requires making decisions in the presence of uncertainty. This course ... will cover material on individual decision making, group decision making, and organizations of decision-makers. The course will present techniques for making better decisions, for understanding how decisions are related to each other, and for managing risk.
Also offered as: ENRE 671. Credit only granted for: ENME 808X, ENRE 671 or ENME 607. Formerly: ENME 808X.

General Mechanical
Overview of applied single- and multi-objective optimization and decision making concepts and techniques with applications in engineering design and/or manufacturing problems. Topics include formulation examples, concepts, optimality conditions, ... unconstrained/constrained methods, and post-optimality sensitivity analysis. Students are expected to work on a semester-long real-world multi-objective engineering project.
Prerequisite: Graduate standing or permission of instructor.

General Mechanical
Kinematics in plane and space; Dynamics of particle, system of particles, and rigid bodies. Holonomic and non-holonomic constraints. Newton's equations, D'Alembert's principle, Hamilton's principle, and equations of Lagrange. Impact and ... collisions. Stability of equilibria.
Prerequisite: ENES221; or students who have taken courses with similar or comparable course content may contact the department; or permission of instructor.

General Mechanical
This course will present classical reliability concepts and definitions based on statistical analysis of observed failure distributions. Techniques to improve reliability, based on the study of root-cause failure mechanisms, will be presented; ... based on knowledge of the life-cycle loadprofile, product architecture and material properties. Techniques toprev ent operational failures through robust design and manufacturing practices will be discussed. Students will gain the fundamentals and skills in the field of reliability as it directly pertains to the designand the manufacture of electrical, mechanical, andelectomechanical products.

Formerly ENPM808J
This course provides an introduction to a field of robotics dedicated to improving the lives of people with disabilities. The course is designed for graduate students wishing to learn more about the rehabilitation robotics, an emerging and ... one of the fastest growing field of robotics. Rehabilitation robotics is the application of robots to overcome disabilities resulting from neurologic injuries and physical trauma, and improve quality of life. In contrast with other sub-specialties and/or courses in robotics, this course considers not only engineering design and development, but also the human factors that make some innovative technologies successful and others commercial failures. Engineering innovation by itself - without considering other factors such as evidence-based R&D and product acceptance – may mean that some technologies don’t become or remain available, or are efficacious to aid their intended beneficiaries. This course differs from biomedical engineering in its focus on improving the quality of life, rather than improving their medical treatment.

Formerly ENPM808K
Define the intersection of human-robot interactions to include human-computer interfaces as well as robotic emotions and facial expressions emulations. The result will provide a basis for students to assess the best approaches for interacting ... effectively with robots.

Summer 2023 Class time/details on ELMS Craig Schlenoff , Zeid Kootbally
Formerly ENPM809B. The course will look at the components of manufacturing robots, including architectures, knowledge representation, planning, control, safety, standards, and human-robot interaction. Students will explore the work that is ... being performed around the world in each of these areas, and will perform small hands-on exercises in class to gain a deeper understanding of how a selected set of these technologies can be applied to real-world challenges. This course will have invited presentations from experts in the field.
Recommended: Prior C++ or Python programming experience.

Machine learning may be used to greatly expand the capabilities of robotic systems, and has been applied to a variety of robotic system functions including planning, control, and perception. Adaptation and learning are particularly important ... for development of autonomous robotic systems that must operate in dynamic or uncertain environments. Ultimately we would like for the robots to expand their knowledge and improve their own performance through learning while operating in the environment (on-line and/or lifelong learning). Robot Learning covers the application of learning techniques including Reinforcement Learning, Learning from Demonstration, and Robot Shaping that may be used with a variety of machine learning paradigms for which data is used to generate (through induction) models that are then used by the robot to perform tasks. A wide variety of paradigms are available to generate models (e.g., CMAC, KNN, MLP, lazy learning, LWR, RBF, deep networks). These learning techniques and paradigms are then combined with traditional robotic control approaches (e.g., motor schema, behavior-based, direct and inverse methods) to create controllers to control the robots while operating in real-world environments. This graduate course will explore the application of machine learning techniques, paradigms, and control design to robotic systems, focusing primarily on key useful representations and model building techniques for application in non-stationary robotic systems.
Formerly: ENPM808F.

This course will cover manufacturing automation and product realization, digital factories, and disruptive manufacturing technologies. The role of additive manufacturing, sustainability, and performance simulation in selected manufacturing ... scenarios will be explored alongside automation strategies for rapid product development.
Formerly: ENPM808P.

As the robotics industry continues to grow and evolve, software's role in these products and systems is also becoming more critical. From embedded controls to advanced perception and learning, software permeates today's robots. Building off ... domain expertise developed in other robotics courses, this course teaches the tools and processes to develop professional quality software for deployed systems and products. Students will learn the best practices of taking new ideas or prototypes, and understanding what it takes to build the complex software that is so important to today’s commercialized robotic systems. The course is split into two parts: the first will review the C++ programming language, object-oriented programming (OOP) concepts, version control, testing, and agile software development processes; the second will introduce the popular Robot Operating System (ROS) framework with intensive programming assignments and projects. Students should be proficient in using Linux, programming with C/C++ and understand the concepts of object-oriented programming.

This is a hand-on course exploring the fundamentals of autonomous navigation for robotic platforms. Students will explore technologies including light detection and ranging (lidar), radar, and computer vision in the context of autonomous navigation. ... Students will perform small hands-on exercises in most classes to gain a deeper understanding of how a selected set of these technologies can be applied to real-world robotic environments. This course requires completion of a semester-long hands-on project employing the course material, data collection and processing, and navigational control of an autonomous robot. Students perform this work in teams of 1-3, which stay together throughout the semester. Specific project details will be provided during the first course lecture.

This hands-on course will introduce students to robot programming. This course is specifically designed for students who have had little to no programming experience in their previous studies to prepare them for other ENPM robotics courses ... that require programming experience. This course will focus on C++ programming and provide a very brief introduction to Linux and the Robot Operating System (ROS). Small projects will be assigned to allow students to apply what they have learned in class.