The travel imagination and the hybrid reality in the wake of colonialism

The “traveling imagination,” is of paramount importance to both western and postcolonial travelers. Since both groups create “travel imaginations” by extensive reading, the nature of the books that inform them must directly affect their travels. A westerner, for example, who reads only colonial-era accounts has the “travel imagination” of a different generation. If all perspectives were represented equally in libraries, the “travel imagination” of a given person would be entirely his/her own. But usually the “traveler’s imagination” is biased by prevailing opinion. Libraries are not democracies, and sometimes extensive reading only indoctrinates the reader with the biases of the canon. Perhaps the following generalization will be helpful. Westerners are able to create “traveling imaginations,” based on the books they trust. But postcolonials, who have reason to be suspicious of what they read, have complicated “traveling imaginations.” Sometimes postcolonial travelers base their “traveling imaginations” on what they read, and sometimes, in opposition to what they read. The books discussed in this thesis, In Patagonia, The Cruise of the Shark, The Happy Isles of Oceania, A Passage to England and The Enigma of Arrival, were first published in, 1977, 1939, 1992, 1971 and 1987, respectively, in what Ali Behdad calls the “age of colonial dissolution.” Perhaps it would be more accurate to say these books are set in the “age of colonial demolition.” For the most part, the empires in these texts are in ruins, or at least in the process of being dismantled. In fact, two of the authors, Nirad Chaudhuri and V.S. Naipaul are canonical post-colonial thinkers.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.