Abstract:  Perception recognition and path planning technologies are investigated in this study to address the various issues faced during the spraying process, such as challenging accurate environmental perception, hard evaluation of wet spraying effect, and complex spraying path planning. Traditional spraying equipments have accumulated several unreliable spraying faults, which lead to inconsistent spraying quality of each ring as well as considerable rebound spalling. To increase the shotcrete robot′s ability to perceive its external environment, a tunnel model based on an axis normalization approach and multiprocess scanning strategy is employed to realize the tunnel environment recognition, vehicle body positioning, and spraying quality perception. Due to the poor adaptability of traditional slurry spraying equipment in complex heterogeneous tunnels, the spraying trajectory cannot be adjusted flexibly. Therefore, a proposal for a multicycle perception recognition and path planning technique is proposed. Furthermore, to reduce the coupling between the shotcrete robot and tunnel excavation method, optimal spraying path planning and continuous spray path planning method are explored and designed to reduce direct spray arch. Technical achievements have been used in projects like Guodashan and Renjiagou tunnels, and notable results, such as a 93% accuracy rate of perception and identification of crosssection arch, a positioning accuracy and arm compensation error within 50 mm, and a 11.9 % comprehensive rebound rate have been achieved.

Key words: shotcrete robot, intellisense, intelligent recognition, adaptive spray, path planning