Bionic tracking method by hand & eye-vergence visual servoing
Tóm tắt
Animals rotate their eyes to gaze at the target prey, enhancing the ability of measuring the distance to the target precisely for catching it. These animals, visual tracking includes the triangular eye-vergence control and their body’s motion control by visual servoing. The research aims to realize a bionic robot tracking performance, in which the body links moves together with eyes’ view orientation. This paper proposed a hand & eye-vergence dual control system which included two feedback loops: an outer loop for conventional visual servoing to direct a manipulator toward a target object and an inner loop for active motion control of binocular cameras to change the viewpoint along with the moving object to give an accurate and broad observation. This research also foused on how to compensate a fictional motion of the target seen by camera images in an eye-in-hand system, where the camera was fixed on the end-effector and moved together with the hand motion. A robust motion-feedforward (MFF) recognition method is proposed to compensate the fictional motion of the target based on the manipulator’s joint velocity, then the real motion of the target seen by camera images is extracted, which can improve the feedback image sensing unit to make the whole servoing system dynamically stable. The effectiveness of the proposed hand & eye-vergence visual servoing method is shown by tracking experiments using a 6-DoF robot manipulator and a 3-DoF binocular vision system.
Tài liệu tham khảo
Nammoto T, Hashimoto K, Kagami S et al (2013) High speed/accuracy visual servoing based on virtual visual servoing with stereo cameras. In: IEEE/RSJ international conference on intelligent robots and systems (IROS), Tokyo, Japan, 3–7 Nov, pp 44–49
Elsamnah F, Sediono W, Khalifa O et al (2014) Multi-stereo camera system to enhance the position accuracy of image-guided surgery markers. In: International conference on computer and communication engineering: emerging technologies via comp-unication convergence, Kuala Lumpur, Malaysia, 23–25 Sept, pp 88–91
Stavnitzky J, Capson D (2001) Mutiple camera model-based 3-D visual servoing. IEEE Trans Robot Autom 16(6):732–739
Dune C, Marchand E, Leroux C (2007) One click focus with eye-in-hand/eye-to hand cooperation. In: IEEE international conference on robotics and automation (ICRA), Roma, Italy,10–14 April, pp 2471–2476
Park DH, Kwon JH, Ha IJ (2012) Novel position-based visual servoing approach to robust global stability under field-of-view constraint. IEEE Trans Ind Electron 59(12):4735–4752
Wilson WJ, Williams Hulls CC, Bell GS (1996) Relative end-effector control using cartesian position based visual servoing. IEEE Trans Robot Autom 12(5):684–696
Cai C, Dean-León E, Somani N et al (2014) 6D image-based visual servoing for robot manipulators with uncalibrated stereo cameras source. In: IEEE/RSJ international conference on intelligent robots and systems (IROS 2014), Chicago, Illinois, 14–18 Sept, pp 736–742
Tahri O, Araujo H, Chaumette F (2013) Robust image-based visual servoing using invariant visual information. Robot Auton Syst 61(12):1588–1600
Xian B, de Queiroz MS, Dawson D et al (2004) Task-space tracking control of robot manipulators via quaternion feedback. IEEE Trans Robot Autom 20(1):160–167
Song W, Natsume T, Minami M (2004) 3-D position/orientation measurement using model-based matching method and GA: proposal of calculation method and evaluation. In: Proceedings of the SICE annual conference, Sapporo, Japan, 4–6 Aug, pp 277–282
Song W, Minami M (2009) Stability/precision improvement of 6-DoF visual servoing by motion feedforward compensation and experimental evaluation. In: IEEE international conference on robotics and automation, Guilin, Guangxi, 18–22 Dec, pp 722–729
Suzuki H, Minami M (2005) Visual servoing to catch fish using global/local GA search. IEEE/ASME Trans Mechatron 10(3):352–357