Tham khảo tài liệu 'sensing intelligence motion - how robots & humans move - vladimir j. lumelsky part 13', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 336 HUMAN PERFORMANCE IN MOTION PLANNING computer mouse. Every time the cursor approaches a labyrinth wall within some small distance that is your radius of vision the part of the wall within this radius becomes visible and so you can decide where to turn to continue the motion. Once you step back from the wall that piece of the wall disappears from the screen. Your performance in this new setting will of course deteriorate compared to the case with complete information above. You will likely wander around hitting dead ends and passing some segments of the path more than once. Because you cannot now see the whole labyrinth there will be no hope of producing a near-optimal solution you will struggle just to get somehow to point T. This is demonstrated in two examples of tests with human subjects shown in Figure . Among the many such samples with human subjects that were obtained in the course of this study see the following sections these two are closest to the best and worst performance respectively. Most subjects fell somewhere in between. While this performance is far from what we saw in the test with complete information it is nothing to be ashamed of the test is far from trivial. Those who had a chance to participate in youth wilderness training know how hard one has to work to find a specific spot in the forest with or without a map. And many of us know the frustration of looking for a specific room in a large unfamiliar building in spite of its well-structured design. Human Versus Computer Performance in a Labyrinth. How about comparing the human performance we just observed with the performance of a decent motion planning algorithm The computer clearly wins. For example the Bug2 algorithm developed in Section operating under the same conditions as for the human subjects in the version with incomplete information produces elegant solutions shown in Figure In case a the robot uses tactile information and in case b it uses vision with a limited .
