We propose video coding that extracts minimum information for robots to reduce data transmission in a robot vision network where a ceiling map is generated from ceiling video from an indoor search robot and shared among search robots. Video signals are conventionally decomposed into several components and only visually significant components are transmitted. We propose that only required components for ceiling map generation and auto localization be designated as the basic layer and that other components be assigned as the enhancement layer. Only the basic layer is transmitted and received in regular communication between the robots. The enhancement layer is additionally transmitted to enable users to browse images. Experiments verified that transmission data volume was reduced by 15%, enabling more users and robots to link up in networks whose communication channel transmission is limited.
This paper proposes a functionally layered video coding for robot vision network. Video signals from mobile robots are regularly transmitted to a remote robot. It uses the video to estimate locations of each of the mobile robots. As the need arises, a person browses the video to check the scenery. In such occasion, the functionally layered video coding regularly transmits the minimum components necessary for the motion estimation by the remote robot. For scenery browsing, only additional components are transmitted on demand. As a result, data volume to be transmitted is reduced in total. The proposed method decomposes the video into frequency bands and bit planes by means of the JPEG 2000. This report investigates the minimum components for the motion estimation in the robot to robot communication. It is confirmed that the proposed method can reduce total data volume of the robot vision network.
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