Abstract
Unmanned aerial vehicles (UAVs) are excellent platforms for detecting and tracking objects of interest on or near the ground due to their vantage point and freedom of movement. This paper presents a cooperative vision-based estimation and tracking system that can be used in such situations. The method is shown to give better results than could be achieved with a single UAV, while being robust to failures. In addition, this method can be used to detect, estimate and track the location and velocity of objects in three dimensions. This real-time, vision-based estimation and tracking algorithm is computationally efficient and can be naturally distributed among multiple UAVs. This chapter includes the derivation of this algorithm and presents flight results from several real-time estimation and tracking experiments conducted on MIT’s Real-time indoor Autonomous Vehicle test ENvironment (RAVEN).
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Bethke, B., Valenti, M., How, J. (2007). Cooperative Vision Based Estimation and Tracking Using Multiple UAVs. In: Pardalos, P.M., Murphey, R., Grundel, D., Hirsch, M.J. (eds) Advances in Cooperative Control and Optimization. Lecture Notes in Control and Information Sciences, vol 369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74356-9_11
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DOI: https://doi.org/10.1007/978-3-540-74356-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74354-5
Online ISBN: 978-3-540-74356-9
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