Read the following passages carefully and answer the questions given at the end of each passage.

PASSAGE 4

The Cyclopses according to mythology were a race of bad tempered and rather stupid one eyed giants. Not perhaps a great portend for a new generation of robots. But Andrew Davison a computer scientist at Imperial College, London, thinks one eye is enough for a robot, provided its brain can think fast enough. For a robot to work autonomously it has to understand its environment. Stereoscopic vision, integrating the images from two eyes looking at the same thing from different angles is one approach to achieve this, but it involves a lot of complicated computer processing. The preferred method these days therefore is Simultaneous Localisation and Mapping (SLAM) which uses sensors such as laser based range finders that see by bouncing beams of light off their surroundings and timing the return. Dr. Davison however wants to replace the range finders which are expensive and fiddly with a digital camera, which is small, cheap, and well understood. With this in mind he is developing ways to use a single moving video camera to create continually updated 3D maps that can guide even the most hyperactive robots on its explorations. His technique involves collecting and integrating images taken from different angles as the camera goes on its travels. The trick is to manage to do this in real time, at frame rates of 100-1,000 per second. The shape of the world pops out easily from laser data because it represents a direct contour map of the surrounding area. A camera captures this geometry indirectly and so needs more (and smarter) computation if it is to generate something good enough for a self - directing robot. The answer is a form of triangulation, tracking features such as points and edges from one frame to the next. With enough measurements of the same set of features from different viewpoints, it is possible if you have a fast enough computer program to estimate their positions and thus by inference the location of the moving camera. However, developing such a program is no mean feat. In the milliseconds between successive frames, relevant information from each fresh image must be extracted and fused with the current map to produce an updated version. The higher the frame rate, the less time there is to do this work.