On-orbit servicing and active debris removal missions are becoming increasingly important to limit the growth of space debris in Earth’s orbit. SmallSats offer a promising option for reducing the cost and risk of these missions, allowing for their expanded use on a wider scale. For these missions to be successful, SmallSats are required to operate at very-close ranges to a target object. Relative visual navigation at this distance still presents a hurdle that needs to be overcome prior to implementing these platforms. This work analyses the suitability of Simultaneous Localization and Mapping (SLAM) for navigation at very-close ranges and proposes a modified algorithm to increase performance. Characterization of this algorithm is performed against a custom generated lab-based image dataset simulating final approach to a satellite. Algorithm performance shows promising results for SLAM use in very-close range environments and presents a first step in the development of this SmallSat navigation technology.