Fire Fighting Tactics with Aerial Hosetype Robot xe2x80x9cDragon Firefighterxe2x80x9d We herein propose the method for developing an xe2x80x9caerial hose type robotxe2x80x9d called the xe2x80x9cDragon Firefighter (DFF)xe2x80x9d that can fly along with the water jet. We focus on realizing a novel concept through which obstacles can be avoided and fire spots can be accessed from a distance, thereby enabling direct firefighting, and evaluating fire suppression ability from a close distance of fire source for practical useage. Using robotics, we aim to extinguish the fire from a distance, simultaneously guaranteeing firefightersu0027 safety. We were able to realize stable floating of a hose of length 2.8 m (total length of 3.6 m), which is twice that of a conventional one, overcoming the height gap of approximately 1.5 m and the size of frontage  mathbf1.0 times mathbf2.5 mathbfm . We demonstrated a fire extinguishing, however the ability of fire extinguishing about DFF was unknown. Hence, we conducted a mist spray experiment from a close distance to validate the cooling effect of water. Considering the aerial nature of our robot, we concluded that a mist spray from its nozzle module will be more effective for extinguishing fires. Finally, we presented the consideration of firefighting tactics using the proposed DFF for practical implementation.

Selfmodeling Tracking Control of Crawler Fire Fighting Robot Based on Causal Network * In this paper, a selfmodeling method based on a causal network is proposed for the tracking control of the Crawler Fire Fighting Robot (CFFR). The method mainly consists of two parts, one is a motion model, based on data driving, learning to establish the correspondence between control signal sequence and vehicle motion, estimating the motion state of the next moment from historical data, eliminating complex CFFR modeling. The other is the tracking network. Based on the simulation data of the motion model, the relationship between the target trajectory and the current control command is learned, which simplifies the design and cumbersome tuning of the complex controller. The effectiveness of the proposed method is verified in both simulated and realworld environments. Qualitative and quantitative experimental results verify the accuracy of the tracking.