Skip to Main Content
Cooperative mobile robots must have knowledge of their positions relative to the group in which they are operating. Common on-board sensors such as laser rangefinders may be used to detect and track other robots with high precision, though limited feature recognition and susceptibility to occlusion reduces the efficacy of this solution alone. Matching multiple robots' laser scans can overcome some of these issues, but requires extensive memory usage and large communication bandwidth. Overhead imaging systems may also be utilized, though sensor nonlinearities, field of view restrictions, and data latency limit such usage. A data fusion method is proposed for dynamically evaluating a mobile robot's position by matching laser scan data to overhead image data.