91 - 100 of 184 results for: ME

Introduction to the philosophy and practice of the Design Impact program. Hands-on design projects are used as vehicles for learning design thinking's tools and methodology. The relationships among technical, human, aesthetic, and business concerns, and drawing, prototyping, and story-telling a will be explored. The focus is on design thinking process and mindsets including: empathy, point of view, ideation, prototyping and testing. For master's students in the Design Impact program only. For a general introduction to design thinking, see ME 377: Design Thinking Studio, taught Autumn and Winter quarters.

This course covers fundamental principles of robotic dexterous manipulation, including kinematics, manipulator and gripper control, motion planning, contact modeling, and grasp stability. It explores robotic perception (vision and tactile) and advanced machine learning techniques (reinforcement learning and learning from demonstration). Students will apply these concepts in a hands-on group project using robotic manipulators for complex tasks. Homework assignments with both analytical and coding components will reinforce the concepts learned in class. Students should feel comfortable in Python and Linux (dual booting on a personal computer may be necessary for some assignments).

Design course focusing on an integrated suite of computer tools: rapid prototyping, solid modeling, computer-aided machining, and computer numerical control manufacturing. Students choose, design, and manufacture individual products, emphasizing individual design process and computer design tools. Structured lab experiences build a basic CAD/CAM/CNC proficiency. Limited enrollment. Prerequisite: ME103 or equivalent and consent of instructor. ME 203 or consent of instructor. By application only, see notes below.

Robotics foundations in modeling, design, planning, and control. Class covers relevant results from geometry, kinematics, statics, dynamics, motion planning, and control, providing the basic methodologies and tools in robotics research and applications. Concepts and models are illustrated through physical robot platforms, interactive robot simulations, and video segments relevant to historical research developments or to emerging application areas in the field. Recommended: matrix algebra.

This graduate-level course will introduce the capabilities, limitations, and state-of-the-art in multimaterial additive manufacturing (AM) methods, with a focus on polymer-based materials. The course will begin with a broader introduction to AM followed by an introduction to fundamentals on polymer-based materials and rheology. The second half of the course will focus on multimaterial AM methods, including reviews of recent literature and a course project in the laboratory. AM methods that will be covered include direct ink writing (DIW), fused filament fabrication (FFF), vat photopolymerization (VP), material jetting (MJ), binder jetting (BJ), and powder bed fusion (PBF). This course requires introductory knowledge of additive manufacturing, working knowledge of Computer Aided Design software, mechanics of materials, fluid dynamics, and mechanical systems design. Attendance and in-class participation is required.

Advanced control methodologies and novel design techniques for complex human-like robotic and bio mechanical systems. Class covers the fundamentals in operational space dynamics and control, elastic planning, human motion synthesis. Topics include redundancy, inertial properties, haptics, simulation, robot cooperation, mobile manipulation, human-friendly robot design, humanoids and whole-body control. Additional topcs in emerging areas are presented by groups of students at the end-of-quarter mini-symposium. Prerequisites: 223A or equivalent.

Concepts and tactics for the design of precision machines including flexures, kinematic design, actuators, sensors, vibration isolation, athermalization and metrology. Hands-on, project based class. Prerequisites ME 103, 203. By application only, see notes below.

Design course focusing on the process of injection molding as a prototyping and manufacturing tool. Coursework will include creating and evaluating initial design concepts, detailed part design, mold design, mold manufacturing, molding parts, and testing and evaluating the results. Students will work primarily on individually selected projects, using each project as a tool to continue developing and exercising individual design process. Lectures and field trips will provide students with context for their work in the Stanford Product Realization Lab. Prerequisite: ME318 or consent of instructors. By application only, see notes below.

This course focuses on how robots can be effective teammates with other robots and human partners. Concepts and tools will be reviewed for characterizing task objectives, robot perception and control, teammate behavioral modeling, inter-agent communication, and team consensus. We will consider the application of these tools to robot collaborators, wearable robotics, and the latest applications in the relevant literature. This will be a project-based graduate course, with the implementation of algorithms in either python or C++.