BACKGROUND: Robotic assistance has been shown to increase instrumentation placement accuracy in open and minimally invasive spinal fusion. These gains have been achieved without increases in operative times, blood loss, or hospitalization duration. However, most work has been done in the degenerative population and little is known of the utility of robotic assistance when applied to spinal trauma. This is largely due to the uncertainty stemming from the disruption of normal anatomy by the traumatic injury. Since the robot depends upon registration for instrumentation guidance according to the fiducials it uses, trauma can introduce unique challenges. The present study sought to evaluate the safety and efficacy of robotic assistance in a consecutive cohort of spine trauma patients. METHODS: All patients with Thoracolumbar Injury Classification and Severity Scale (TLICS) >4 who underwent robot-assisted spinal fusion using the Globus ExcelsiusGPS at a single tertiary care center for trauma between 2020 and 2022 were identified. Demographic, clinical, and surgical data were collected and analyzed; the primary endpoints were operative time, fluoroscopy time, estimated blood loss, postoperative complications, admission time, and 90-day readmission rate. The paired t-test was used to compare differences between mean values when looking at the number of surgical levels. RESULTS: Forty-two patients undergoing robot-assisted spinal surgery were included (mean age 61.3±17.1 year; 47% female. Patients were stratified by the number of operative levels, 2 (n = 10), 3-4 (n = 11), 5 to 6 (n = 13), or >6 (n = 8). There appeared to be a positive correlation between number of levels instrumented and odds of postoperative complications, admission duration, fluoroscopy time, and estimated blood loss. There were no instances of screw malposition or breach. CONCLUSIONS: This initial experience suggests robotic assistance can be safely employed in the spine trauma population. Additional experiences in larger patient populations are necessary to delineate those traumatic pathologies most amenable to robotic assistance.