Optimizing Cleaning Robot's Navigation through Ray Casting Algorithms for Efficient Path Planning

Presenter

James Espaillat

Group Members

Aissatou Amadou

Campus

Quinsigamond Community College

Sponsor

Hao Loi, Department of Computer Science, Quinsigamond Community College

Schedule

Session 2, 11:30 AM - 12:15 PM [Schedule by Time][Poster Grid for Time/Location]

Location

Poster Board A19, Campus Center Auditorium, Row 1 (A1-A20) [Poster Location Map]

Abstract

This project proposes use of ray casting algorithms for enhancement of a cleaning robot’s navigation system in enabling it to follow straight-line paths while avoiding obstacles. The ray casting technique, a cornerstone of computer graphics rendering, will be employed to cast rays across the cleaning space. This method ensures comprehensive coverage and efficient movement planning. The project will adapt similar concepts of elevation maps on terrain mapping to optimize the robot’s environmental understanding and path planning. The integration of sensor data will complement the ray casting algorithms, allowing the robot to make informed decisions and optimize it’s cleaning path. The combined use of these technologies will enable the robot to navigate along straight lines, efficiently turning and continuing in parallel lines upon encountering obstacles, thus maximizing cleaning efficiency and coverage. We expect the results to refute the null hypothesis, by improving the speed, cleaning, and accuracy. the implication of this cleaning robot will revolutionize the cleaning robot industry. The code may also advance other moving robot servers and mechanical robots such as 3D robots builders and medical service robots. Furthermore, the successful implementation of these advancements could pave the way for more efficient and effective utilization of autonomous cleaning robots in various real-world scenarios.

Keywords

Efficiency, Ray Traversal, Space Filling Curves, Path Planning Algorithms, Environmental Understanding

Research Area

Computer Science

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