Balance-bot

Research on inverted pendulum has gained momentum over the last decade on a number of robotic laboratories over the world; due to its unstable proprieties is a good example for control engineers to verify a control theory. To verify that the pendulum can balance we can make some simulations using a closed-loop controller method such as the linear quadratic regulator or the proportional–integral–derivative method. Also the idea of robotic teleoperation is gaining ground. Controlling a robot at a distance and doing that precisely. However, designing the tool to takes the best benefit of the human skills while keeping the error minimal is interesting, and due to the fact that the inverted pendulum is an unstable system it makes a compelling test case for exploring dynamic teleoperation. Therefore this thesis focuses on the construction of a two-wheel inverted pendulum robot, which sensor we can use to do that, how they must be integrated in the system and how we can use a human to control an inverted pendulum. The inverted pendulum robot developed employs technology like sensors, actuators and controllers. This Master thesis starts by presenting an introduction to inverted pendulums and some information about related areas such as control theory. It continues by describing related work in this area. Then we describe the mathematical model of a two-wheel inverted pendulum and a simulation made in Matlab. We also focus in the construction of this type of robot and its working theory. Because this is a mobile robot we address the theme of the teleoperation and finally this thesis finishes with a general conclusion and ideas of future work.

Inexpensive solution for real-time video and image stitching

Image stitching is the process of joining several images to obtain a bigger view of a scene. It is used, for example, in tourism to transmit to the viewer the sensation of being in another place. I am presenting an inexpensive solution for automatic real time video and image stitching with two web cameras as the video/image sources. The proposed solution relies on the usage of several markers in the scene as reference points for the stitching algorithm. The implemented algorithm is divided in four main steps, the marker detection, camera pose determination (in reference to the markers), video/image size and 3d transformation, and image translation. Wii remote controllers are used to support several steps in the process. The built‐in IR camera provides clean marker detection, which facilitates the camera pose determination. The only restriction in the algorithm is that markers have to be in the field of view when capturing the scene. Several tests where made to evaluate the final algorithm. The algorithm is able to perform video stitching with a frame rate between 8 and 13 fps. The joining of the two videos/images is good with minor misalignments in objects at the same depth of the marker,misalignments in the background and foreground are bigger. The capture process is simple enough so anyone can perform a stitching with a very short explanation. Although real‐time video stitching can be achieved by this affordable approach, there are few shortcomings in current version. For example, contrast inconsistency along the stitching line could be reduced by applying a color correction algorithm to every source videos. In addition, the misalignments in stitched images due to camera lens distortion could be eased by optical correction algorithm. The work was developed in Apple’s Quartz Composer, a visual programming environment. A library of extended functions was developed using Xcode tools also from Apple.