Abstract
We have been participating in the Tsukuba Challenge, an open experiment involving autonomous robots, since 2014. The technology of our robot has stabilized, and our robot has continued to win the Tsukuba Mayor Prize from 2018 to 2021 without changing the basic configuration of the body and navigation software. Here, we report the robot’s structure as the project’s current completed form. Our robot is designed with the policy of selecting the most rational technology (appropriate technology) to achieve the purpose, even if it is not the latest. For example, we used image-like two-dimensional data instead of a three-dimensional point cloud in map matching for robot positioning. For pedestrian signal recognition, which was required to perform an optional task, we did not use deep learning but rather conventional color image processing. These techniques are advantageous for balancing the execution time and accuracy required in the challenge.
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