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We consider a realistic wireless sensor deployment strategy by which mobile robot deploys sensor nodes when it moves along the linear backbone network with some branches. Because of its finite load capacity, the robot has to repeatedly move back to the position where all sensors are temporarily stored and reload sensor nodes, which leads to the robot has to travel the path many times and consumes more energy. We present a Shortest Traveling Path for Robot (STPR) algorithm by which the robot can reduce the traveling path and achieve the required coverage. All nodes are stored at the temporary starting point and mobile robot continuously loads sensors and moves to the destination, dropping some sensor to meet the basic coverage and connectivity requirements. The mobile robot arrives at the far intersection and deploys sensors along the branches in accordance with the algorithm rules, and then returns the recent branch when having enough sensors. Otherwise the robot moves back and deploys sensors on the back path. The robot reloads sensors and repeats the deployment process until all the branches and backbone is finished. The paper proves that the algorithm is effective compared with the common methods. Simulation results show that the algorithm effectively reduces the moving distance at the randomly generated network.