Considering the recent implementation of lung cancer screening guidelines, it is crucial that small pulmonary nodules are accurately diagnosed. There is a significant need for quick, precise, and minimally invasive biopsy methods, especially for patients with small lung lesions in the outer periphery. Robotic bronchoscopy (RB) has recently emerged as a novel solution. The purpose of this study was to evaluate the accuracy of RB compared to the existing standard, electromagnetic navigational bronchoscopy (EM-NB). A prospective, single-blinded, and randomized-controlled study was performed to compare the accuracy of RB to EM-NB in localizing and targeting pulmonary lesions in a porcine lung model. Four operators were tasked with navigating to four pulmonary targets in the outer periphery of a porcine lung, to which they were blinded, using both the RB and EM-NB systems. The dependent variable was accuracy. Accuracy was measured as a rate of success in lesion localization and targeting, the distance from the center of the pulmonary target, and by anatomic location. The independent variable was the navigation system, RB was compared to EM-NB using 1:1 randomization. Of 75 attempts, 72 were successful in lesion localization and 60 were successful in lesion targeting. The success rate for lesion localization was 100% with RB and 91% with EM- NB. The success rate for lesion targeting was 93% with RB and 80% for EM-NB. RB demonstrated superior accuracy in reaching the distance from the center of the lesion, at 0.62mm compared to EM-NB at 1.28mm (p = 0.001). Accuracy was improved using RB compared to EM- NB for lesions in the LLL (p = 0.025), LUL (p < 0.001), and RUL (p < 0.001). Our findings support RB as a more accurate method of navigating and localizing small peripheral pulmonary targets when compared to standard EM-NB in a porcine lung model. This may be attributed to the ability of RB to reduce substantial tissue displacement seen with standard EM-NB navigation. As the development and application of RB advances, so will the ability to accurately diagnose small peripheral lung cancer nodules, providing patients with early-stage lung cancer the best possible outcomes.