This thesis aimed to assess the feasibility of using an off-the-shelf virtual reality tracking system as a low cost precision pose estimation solution for robotic operations in both indoor and outdoor environments. Such a tracking solution has the potential of assisting critical operations related to planetary exploration missions, parcel handling/delivery, and wildfire detection/early warning systems. The boom of virtual reality experiences has accelerated the development of various low-cost, precision indoor tracking technologies. For the purpose of this thesis we choose to adapt the SteamVR Lighthouse system developed by Valve, which uses photo-diodes on the trackers to detect the rotating IR laser sheets emitted from the anchored base stations, also known as lighthouses. Some previous researches had been completed using the first generation of lighthouses, which has a few limitations on communication from lighthouses to the tracker. A NASA research has cited poor tracking performance under sunlight. We choose to use the second generation lighthouses which has improved the method of communication from lighthouses to the tracker, and we performed various experiments to assess their performance outdoors, including under sunlight. The studies of this thesis have two stages, the first stage focused on a controlled, indoor environment, having an Unmanned Aerial Vehicle (UAS) perform repeatable flight patterns and simultaneously tracked by the Lighthouse and a reference indoor tracking system, which showed that the tracking precision of the lighthouse is comparable to the industrial standard indoor tracking solution. The second stage of the study focused on outdoor experiments with the tracking system, comparing UAS flights between day and night conditions as well as positioning accuracy assessments with a CNC machine under indoor and outdoor conditions. The results showed matching performance between day and night while still comparable to industrial standard indoor tracking solution down to centimeter precision, and matching simulated CNC trajectory down to millimeter precision. There is also some room for improvement in regards to the experimental method and equipment used, as well as improvements on the tracking system itself needed prior to adaptation in real-world applications. / Master of Science / This thesis aimed to assess the feasibility of using an off-the-shelf virtual reality tracking system as a low cost precision pose estimation solution for robotic operations in both indoor and outdoor environments. Such a tracking solution has the potential of assisting critical operations related to planetary exploration missions, parcel handling/delivery, and wildfire detection/early warning systems. The boom of virtual reality experiences has accelerated the development of various low-cost, precision indoor tracking technologies. For the purpose of this thesis we choose to adapt the SteamVR Lighthouse system developed by Valve, which uses photo-diodes on the trackers to detect the rotating IR laser sheets emitted from the anchored base stations, also known as lighthouses. Some previous researches had been completed using the first generation of lighthouses, which has a few limitations on communication from lighthouses to the tracker. A NASA research has cited poor tracking performance under sunlight. We choose to use the second generation lighthouses which has improved the method of communication from lighthouses to the tracker, and we performed various experiments to assess their performance outdoors, including under sunlight. The studies of this thesis have two stages, the first stage focused on a controlled, indoor environment, having an Unmanned Aerial Vehicle (UAS) perform repeatable flight patterns and simultaneously tracked by the Lighthouse and a reference indoor tracking system, which showed that the tracking precision of the lighthouse is comparable to the industrial standard indoor tracking solution. The second stage of the study focused on outdoor experiments with the tracking system, comparing UAS flights between day and night conditions as well as positioning accuracy assessments with a CNC machine under indoor and outdoor conditions. The results showed matching performance between day and night while still comparable to industrial standard indoor tracking solution down to centimeter precision, and matching simulated CNC trajectory down to millimeter precision. There is also some room for improvement in regards to the experimental method and equipment used, as well as improvements on the tracking system itself needed prior to adaptation in real-world applications.