CS 5758

CS 5758

Course information provided by the Courses of Study 2024-2025.

Creating robots capable of performing complex tasks autonomously requires one to address a variety of different challenges such as sensing, perception, control, planning, mechanical design, and interaction with humans. In recent years many advances have been made toward creating such systems, both in the research community (different robot challenges and competitions) and in industry (industrial, military, and domestic robots). This course gives an overview of the challenges and techniques used for creating autonomous mobile robots. Topics include sensing, localization, mapping, path planning, motion planning, obstacle and collision avoidance, and multi-robot control.

When Offered Spring.

Permission Note Enrollment limited to: graduate students.

Outcomes
  • Students will be able to understand and implement localization and mapping algorithms using different sensor modalities.
  • Students will be able to generate a path and the motion for a robot moving around an area with obstacles.
  • Students will be able to understand and implement the concepts of different approaches for motion planning such as roadmaps, feedback control, and sampling based methods.
  • Students will be able to apply the tools learned in the class to physical robots.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one laboratory. Combined with: CS 4758ECE 4180ECE 5772MAE 4180MAE 5180

  • 4 Credits Graded

  • 19950 CS 5758   LEC 001

    • TR
    • Jan 21 - May 6, 2025
    • Bizyaeva, A

  • Instruction Mode: In Person

  • 19951 CS 5758   LAB 421

    • T
    • Jan 21 - May 6, 2025
    • Staff

  • Instruction Mode: In Person

  • 19952 CS 5758   LAB 431

    • W
    • Jan 21 - May 6, 2025
    • Staff

  • Instruction Mode: In Person

  • 19953 CS 5758   LAB 441

    • R
    • Jan 21 - May 6, 2025
    • Staff

  • Instruction Mode: In Person

  • 19954 CS 5758   LAB 451

    • F
    • Jan 21 - May 6, 2025
    • Staff

  • Instruction Mode: In Person