Formation control has been a popular research topic in recent years. This is primarily due to the the use of formation control to coordinate the movement of a swarm of robots. In this paper, with the primary objective of guaranteeing image overlap, a novel bird flocking inspired formation control algorithm was developed to control a swarm of unmanned aerial vehicles (UAVs). Our approach uses only stereo cameras, global positioning system (GPS), and inertial measurement units (IMUs), and removes the need of feature or pattern matching. By utilizing stereo cameras, virtual tracking points can be calculated. The convergence of these tracking points are chosen as the primary formation control goal because if the virtual tracking points are converged, it is guaranteed that the field of view of the cameras of the various UAVs always have some overlap. This allows for different types of stitching methods to be used to form a larger image with no gaps, depending on the configuration of tracking points. Five different control algorithms were developed: direct method, proportional integral derivative, bang-bang, short window model predictive, and long window model predictive. The formation controller was tested in three simulation environments to verify the robustness and the effectiveness of our algorithm.

Researchers have extensively explored indoor localization in recent years. Robotic applications often require precise positioning, which is difficult when access to a GPS is limited or compromised. Many of the existing approaches require either prior knowledge of the local environment and fixed landmarks or complex and expensive hardware to achieve the necessary degree of accuracy. In this article, we examine the use of the HTC virtual reality hardware along with our novel approach, VIVEPOSE, to perform indoor robotic localization. We then compare the accuracy of our proposed indoor localization system to current approaches that use traditional odometry sensor-based localization. Finally, we present and demonstrate a leader-follower approach using VIVEPOSE and show how the HTC Vive tracker can be successful for indoor localization for a robotics application.