Final Year Project

Project Title

Uncertainty in Odometry Position Estimate of a Bicycle Kinematic Model (Theory and Simulation)

Description

State estimation in the presence of noise is a common problem encountered when trying to determine the value of a system’s state (such as temperature, pressure, etc. using measurements obtained from sensors. The issue is that these measurements are often corrupted by various sources of noise, such as electrical interference or random fluctuations. While estimation algorithms can be used to try and determine the true state value, they can’t provide an exact value due to the presence of this noise. This means that the estimated value will have some degree of error, which can accumulate over time with repeated measurements. The goal of this project is to use the estimated value develop a mathematical expression that can help quantify the uncertainty in the system’s state. This approach, known as covariance analysis, can help us better understand the sources of error in the system and potentially even calibrate the system to minimize these errors and improve the accuracy of the estimation.