Vision-based leader-follower formations with limited information

Autor:	Nikolaos Papanikolopoulos, Hyeun Jeong Min, Andrew Drenner
Rok vydání:	2009
Předmět:	Engineering business.industry Diagonal Stability (learning theory) law.invention Computer Science::Robotics Extended Kalman filter law Position (vector) Pinhole camera Trajectory Robot Computer vision Feedback linearization Artificial intelligence business
Zdroj:	ICRA
DOI:	10.1109/robot.2009.5152261
Popis:	This paper presents a new vision-based leader-follower formation algorithm where the leader's trajectory is unknown to the robots which are following. Formation schemes in straight lines and diagonal formations are introduced which are both stable and observable in the presence of limited views. The algorithms are novel since they only use local image measurements through a pinhole camera to estimate the leader's position. This approach does not require specialized markings nor extensive robot communications. The algorithms are also decentralized. We apply an input-output feedback linearization for system stability and utilize an Extended Kalman Filter (EKF) for estimation. Simulations illustrate how the proposed formation controls work. Real experiments utilizing multiple miniature robots are also presented and illustrate the challenges associated with noisy images in real-world applications.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a538379cdc2a07739e498f31bb230a67 https://doi.org/10.1109/robot.2009.5152261 Zobrazit plný text záznamu