Current practices for imaging foreign bodies within the human body use radiographic techniques, which present several limitations and health problems for both the operator and the patient. Alternatives for locating these foreign bodies are being studied, focusing on the use of magnetometers, such as GMI and GMR, to measure the magnetic field intensity of metallic objects. To develop a portable device that uses a magnetometer capable of identifying the magnetic field intensity of a metallic foreign body, it is essential that the positioning of this device is mapped with high precision and replicability, thus ensuring greater safety for the patient. This dissertation aims to study inertial navigation methods, using an IMU (Inertial Measurement Unit) to estimate position through acceleration and rotational velocity, and visual odometry, which uses a camera to estimate position through a sequence of images of a given trajectory. Comparative studies between the two methodologies were carried out, highlighting the main sources of error of each and their advantages and disadvantages for the desired application. The IMU data and videos were collected using a Raspberry Pi inside a 3D-printed box that fits into a straight aluminum rail. This setup reduced the main sources of human error, allowing analyses with fewer degrees of freedom. After the analyses with the aluminum rail, additional tests involving more degrees of freedom were conducted using curved 3D-printed rails and freehand, aiming to verify the performance of the methodologies in situations closer to the final application: a portable device for localizing foreign bodies.