COMPUTER MODELING AND SIMULATION OF AUTONOMOUS VEHICLES AND ROBOTS

Name: COMPUTER MODELING AND SIMULATION OF AUTONOMOUS VEHICLES AND ROBOTS
Availability: OutOfStock

ME 468

课程描述

Introduction to the Robot Operating System (ROS). Concepts of vehicle dynamics modeling and simulation, with focus on tire, suspension, steering system, and powertrain modeling. Simulation of sensors (camera, lidar, radar, GPS, IMU). Terramechanics modeling for mobility on deformable terrains. Introduction to the autonomy stack (sensing, perception, planning, and control). Elements of artificial intelligence in autonomy. Elements of verification and validation.

先修课程

ME 459 and (COMPSCI 200 , COMPSCI 220 , COMPSCI 300 , 301, 302, COMPSCI 320 , or placement into COMPSCI 300 ), graduate/professional standing, or member of Engineering Guest Students

满足要求

This course does not satisfy any prerequisites.

学分

未报告

开课时间

未报告

平均绩点

3.79

与历史数据相比无变化

完成率

100%

与历史数据相比无变化

A率

76.92%

与历史数据相比无变化

班级规模

与历史数据相比无变化

Cumulative Grade Distribution

教师 (2026 Summr)

按评分排序，数据来自 Rate My Professors

相似课程

MARINE ROBOTICS

ME 578

Modeling, control, perception, and navigation of autonomous marine robots, including Autonomous Surface Vehicles (ASVs) and Autonomous Underwater Vehicles (AUVs). Core topics include kinematics, dynamics, optimal control, state estimation, perception, communication, and guidance tailored for marine robotic systems. Development and testing of dynamic models, controllers, and perception algorithms on simulated/real marine robot platforms.

INTRODUCTION TO FEEDBACK CONTROL OF AUTONOMOUS SYSTEMS

EMA/ME 458

Feedback control theory fundamentals; numerical optimal control algorithms underpinning autonomous systems; quadcopter kinematics dynamics; quadcopter control and trajectory planning; hands-on labs on a nano quadcopter platform.

CONNECTED AND AUTOMATED TRANSPORTATION SYSTEMS

CIVENGR 570

Connected vehicle and automated vehicle technologies; comprehensive studies of sensing, trajectory planning, and vehicle control within the context of the automated vehicle; consideration of pertinent development and technologies in this field.

INTRODUCTION TO ROBOTICS

ECE/ME 439

Hands-on introduction to key concepts and tools underpinning robotic systems in use and development today. Intended to give students the tools to understand robotic systems, to explore robotics for their own purposes, and to pursue advanced study in the field. Students are expected to have familiarity with a high level programming language such as Python (recommended), MATLAB, Java or Julia.

ADVANCED ROBOTICS: MODERN MOTION PLANNING, ESTIMATION, AND CONTROL

ME 738

Rigid body models of robots, constraints and contact, motion planning methods including sampling based, trajectory optimizations, state estimation algorithms including linear observers and filters, Kalman filters, optimization-based filters, feedback control methods including linear controls, Impedance Control, optimization-based controllers, Differential Dynamic Programming, Lyapunov Analysis and Design, and Underactuations. Knowledge of robotic systems [such asE C E/M E 439andE C E/M E 441] is strongly recommended.