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Explore advanced robotics topics such as path planning and apply them to a mobile robot in an open-ended project.

Robotics 2

Recommended Prior Knowledge and Skills

  • Linear algebra

    • Multiplication of matrices and vectors

    • Manipulation of matrices (inverse, transpose)

  • Familiarity with a programming language

    • MATLAB

    • Python

  • Linear time-invariant (LTI) systems

    • Familiarity with transfer functions

    • Knowledge of basic LTI characteristics

  • Differential equations

    • Familiarity with definition and solution of differential equations up to second order

  • Optimization

    • Familiarity with defining optimization problems

    • Familiarity with some optimization solution techniques

  • Robotics 1

    • Forward and inverse kinematics

    • Jacobian matrix

Desired Course Outcomes
Students will be able to understand and apply:

  • Localization

  • Kalman filter
  • Mapping
  • Simultaneous localization and mapping (SLAM)
  • Motion planning
    • Bug algorithms
    • Potential field method
    • Sampling based approaches: PRM, RRT
  • Distance calculation
  • Formation control
  • Closed kinematic chains
  • Grasping and force control
  • Point contact with and without friction
Course Deliverables

  • Weekly quizzes

  • Four mini projects

    • Intro to ROS

    • Utilizing sensors
    • SLAM
    • "New task"

  • 6000 level only

    • Additional quiz questions

    • Research paper summary

About The Robot

  • Rosmaster X3 from Yahboom

  • Four omni-directional wheel mobile robot
  • Equipped with Nvidia's Jetson Nano
  • Equipped with RGB-D camera
  • Equipped with LIDAR sensor
  • Equipped with voice module
  • Python and ROS capable
Some Past Project "New Tasks"

  • SLAM with multiple robots

  • Platooning using color tracking
  • Search-and-rescue: face detection and rendezvous
  • Multi-robot coordination
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