The application of robots reduces repetitive and dangerous tasks for humans, especially the spraying robot, because many spraying materials are corrosive, toxic, and harmful. This paper designs the motion trajectory planning of the material spraying service robot. With the increasing demand for technology, there are strict requirements for the uniformity and thickness of spraying. In view of this, this paper proposes an algorithm for modeling kinematics using a joint screw and optimizes the modeling algorithm using particle swarm optimization. This makes the industrial spraying robot more intelligent and more capable of completing high-standard tasks. The experimental results in this paper show that when the spraying radii on the large-curvature cone surface are 44.5 and 49.5 mm, respectively, the coating distribution in the intersection area of the curved surfaces can be well controlled, and the optimized algorithm can better plan the path of the spraying robot.

With the rapid development of the market economy, location information services have shifted from outdoor to indoor, requiring higher system accuracy. Indoor positioning and control is an indispensable technical support for mobile home service robots to perform system tasks, and this technology is also an important parameter that marks the level of intelligence of a home service robot. However, in indoor places, how to obtain the target node location information timely and accurately and how to control and path planning should be the first issues to be considered in the design of home robots at this stage. This article gave a brief overview of the current indoor positioning technology and control, analyzed the more widely and frequently used indoor positioning methods, and deeply studied the ultrasonic positioning technology. On this basis, a mobile home service robot system was designed, and simulation experiments were carried out, respectively, to test the receiving time and arrival time of the node signal, the node positioning accuracy, the optimal degree of route planning, and the absolute and relative errors of navigation and path estimation. The experimental results showed that the accuracy of the robot system positioning proposed in this article reached more than 80%, and the relative error was only 4.21%, which verified its feasibility and effectiveness in practical applications. Popularizing it in the market can effectively improve the system performance and intelligence of home service robots.

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