Document Type
Honors Thesis
Abstract
For a load-carrying, stair-climbing robot, it is critical that the robot moves accurately for the safety and well-being of the users and observers nearby. Most systems in the world are nonlinear, including the dynamics of the robot, so having the ability to represent nonlinear systems with linear approximations is an important part of engineering. An extended Kalman filter can perform linear approximations, so it will be used to linearize the robot’s position in space, as sensed by sonar sensors that are on the robot. The extended Kalman filter will be designed to filter out noise on a set of test data as well as provide an improved estimation of the robot’s position. The end result is that the robot’s capabilities will be improved, and the filter will in turn provide a valuable addition that would make this robot even more attractive in the market for customers.
Publication Date
5-1-2021
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Pavlik, Heather, "EXTENDED KALMAN FILTER IMPLEMENTATION ON A LOAD-CARRYING, STAIR-CLIMBING ROBOT" (2021). 2021 Spring Honors Capstone Projects. 52.
https://mavmatrix.uta.edu/honors_spring2021/52