Graduate Coursework Portfolio
The main sections on this page outline graduate courses that contained a substantial project, analysis, or implementation component.
Contents
Overview
Each course is documented in a similar fashion with a few key components. First, the course descriptions are listed to provide context regarding the objectives of the course. [1] Then, the major coursework is denoted by a title in bold-faced type following by a bullet list of key outcomes. The remainder of each course section provides a glimpse of the project. Finally, additional relevant coursework is listed along with course descriptions.
Wearable Mechatronic Devices for Rehabilitation (MAE 501)
The student will undertake their 3 credit independent study under faculty direction (Venkat Krovi PhD, Mechanical and Aerospace Engineering) with additional domain expertise provided by professors from Rehabilitation/Exercise Science departments on an experimental, theoretical, or applied problem [redacted] The student will be responsible in assisting with the development of and/or ongoing research projects. This may involve piloting new hardware and software configurations with emphasis on acquiring data from persons with dysfunction and integrating the device (with Matlab) for data extraction, post-processing and analysis. [2]
Development of a Home-Based Stroke Rehabilitation System on Mobile Electronic Consumer Devices
- Design, fabricate and implement an IMU-based motion analysis system for upper-limb physical therapy applications
- Meet requirements of the state-of-the-art in clinical physical therapy
- Fully document the technical aspects of electro-mechanical design analysis and hardware & software design details
- Deliver a functional prototype with live demonstration of the integrated system
Analytical Dynamics (MAE 562)
Review of Newtonian mechanics for systems of particles. Lagrange's equations of motion for conservative and nonconservative systems. Variational mechanics and Hamilton's principle. Application to various nonlinear problems and specifically to the two-body problem and celestial mechanics. The kinematics and dynamics of rigid bodies. Euler's equations of motion. Application to gyroscopic motion. Introduction to Hamilton's equations of motion. The linearized theory of small oscillations and associated matrix formulations. [1]
- Modeling, analysis, and design of dynamical mechanical systems in three dimensional space
- Spatial descriptions of translational and rotational kinematics (position, velocity, and acceleration)
- Dynamics formulation by methods of, Newton-Euler, Euler-Lagrange, Hamilton
- Emphasis on qualitative assessment of the anaytical equations of motion rather than diagnostic interpretation of computational/numerical simulation results
Computer-Aided Design Applications (MAE 577)
Engineering design and analysis using state-of-the-art computer software tools. Emphasis on the overall product development cycle and simultaneous engineering, including conceptual design, variational geometry, representation, creation and manipulation of solid models, assembly design integrated kinematic and finite element analyses, re-design, geometric dimensioning and tolerancing, and NC programming. [1]
- Comprehensive treatment of standard methodology in numerical representations of geometric objects in three dimensional space
- Homogeneous transformations on objects in three dimensions
- Curve and surface interpolation and aproximation
- Basic operations on parameterized geometric objects
Robotic Algorithms (CSE 568)
Course description is currently unavailable. [3]
The official course description is not live online. This may update in the future. The following has been taken from the lecture slides from the introductory class. [4]
- Class Outline
- Robot Mobility
- Legged/wheeled locomotion
- Forward/inverse kinematics
- Simple Control
- Sensing/Perception
- Ranging
- Vision
- Localization and Mapping
- Bayesian Estimation
- Planning and Navigation
- Robot Coordination (maybe)
- Student Expectation
- Expect moderate to heavy load – on average 10 hrs a week, sometimes more
- Learn the theory, do it in practice
- Math: Trigonometry, probability, CS theory
- Programming: C/C++/Java/Python
- [redacted]
- Class Emphasis
- Introduction to robots/robotics
- Theory and practice – learn by doing
- Algorithms/tools that have applications on other CSE and related fields
- Exciting times to learn about robots – have fun!
Computational implementation of mobile robot sensing, actuation, and control using Robot Operating System (ROS)
- Implement algorithms in ROS subsequent to theoretical introduction in lecture
- Theoretical concepts and algorithms implemented programmatically include:
- Mobile robot position and velocity kinematics and control
- State estimation and observation with various sensor models
- Select localization and mapping algorithms
Systems Analysis 1 (MAE 571)
Development of mathematical techniques for the analysis of systems in the time domain. Introduction to state space concepts. Review of matrices and vectors. Vector spaces. Coordinate transformation. Jordan canonical form. State-space representation of control systems. Solutions of state space equations. Controllability and observability. Feedback control structures. [1]
Linear Control of a Serial Robotic Manipulator
- Perform system analysis, controller and observer design, and performance analysis using Matlab
- Formulate and analyze the nonlinear plant's mathematical model
- Design linear controllers and observers for various combinations of actuator and sensor configuration
- Evaluate performance of controllers acting on the linearized and nonlinear plant models
Optimization in Engineering Design (MAE 550)
Optimization techniques with applications in various aspects of engineering design. Concepts of design variables, constraints, objective functions, penalty functions, Lagrange multipliers. Techniques for solving constrained and unconstrained optimization problems: classical approaches, steepest descent, conjugate directions, conjugate gradient, controlled random searches, etc. Discussion of generalized reduced gradient, sequential linear programming, and recursive quadratic programming strategies. Computer implementation of optimization schemes. Applications and examples in the design of engineering components and systems. [1]
Optimal Path Planning in a Constrained Workspace for Serial Robotic Manipulator
- Develop an optimization scheme for robot path planning in the presence of obstacles using Matlab and C++
- Formulate a generalized kinematic model of a spatial manipulator and end effector path
- Formulate objective function and constraints with a focus on leveraging convexity
- Solve the feasibility problem using a successive convex approximation of the optimization problem
Other Courses
Engineering Analysis 1 (MAE 507)
Linear algebra, linear spaces and applications to ordinary differential equations, introduction to dynamical systems, bifurcations and chaos, Green's functions and boundary value problems, adjoint operators, alternative theorems, orthogonal expansions, Sturm - Liouville systems. [1]
MAE 501 (in progress)
This coursework is ongoing and will be reported in the near future.
References
- ↑ 1.0 1.1 1.2 1.3 1.4 1.5 Graduate Courses - UB Mechanical and Aerospace Engineering "Graduate Course Descriptions"; Department of Mechanical and Aerospace Engineering, University at Buffalo - SUNY; Fetched: September 2015; Source: http://www.mae.buffalo.edu/graduate/course_descriptions.php
- ↑ MAE 501 Course Description; Venkat Krovi; Department of Mechanical and Aerospace Engineering, University at Buffalo - SUNY; Fall 2015
- ↑ Courses - UB Computer Science and Engineering "CSE Graduate Course Offerings"; Department of Computer Science and Engineering, University at Buffalo - SUNY; Fetched: September 2015; Source: http://www.cse.buffalo.edu/graduate/courses.php
- ↑ CSE 468/568: Robotic Algorithms "Lecture 1: Intro"; Professor Karthik Dantu; Department of Computer Science and Engineering, University at Buffalo - SUNY; Spring 2015
