A Camera Calibration Method Based on Plane Grid Points

Zhang, Bao Feng; Tian, Xiu; Zhang, Xiaoling

doi:10.4028/www.scientific.net/amr.230-232.723

Cited by 1 publication

(1 citation statement)

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“…In such a case, there may exist distortions in those out-off-center positions for the binocular vision cameras. Such distortions typically include the radial distortion, centrifugal distortion, and thin prism distortion, among which the radial distortion is regarded to be the factor contributing the most [24,25]. Since the radial distortion is typically regarded to be symmetrical relative to optical axis, two new parameters δx and δy, as shown below, are introduced to correct the pinhole system, {δx=k1x(x2+y2)δy=k2y(x2+y2), where (x,4pty) is the coordinate of any imaging point, and k1 and k2 are distortion coefficients in the radial direction.…”

Section: Library Robot Structure and Its Vision Systemmentioning

confidence: 99%

Positioning, Navigation, and Book Accessing/Returning in an Autonomous Library Robot using Integrated Binocular Vision and QR Code Identification Systems

Zhao

Wan

et al. 2019

Sensors

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With rapid advancements in artificial intelligence and mobile robots, some of the tedious yet simple jobs in modern libraries, like book accessing and returning (BAR) operations that had been fulfilled manually before, could be undertaken by robots. Due to the limited accuracies of the existing positioning and navigation (P&N) technologies and the operational errors accumulated within the robot P&N process, however, most of the current robots are not able to fulfill such high-precision operations. To address these practical issues, we propose, for the first time (to the best of our knowledge), to combine the binocular vision and Quick Response (QR) code identification techniques together to improve the robot P&N accuracies, and then construct an autonomous library robot for high-precision BAR operations. Specifically, the binocular vision system is used for dynamic digital map construction and autonomous P&N, as well as obstacle identification and avoiding functions, while the QR code identification technique is responsible for both robot operational error elimination and robotic arm BAR operation determination. Both simulations and experiments are conducted to verify the effectiveness of the proposed technique combination, as well as the constructed robot. Results show that such a technique combination is effective and robust, and could help to significantly improve the P&N and BAR operation accuracies, while reducing the BAR operation time. The implemented autonomous robot is fully-autonomous and cost-effective, and may find applications far beyond libraries with only sophisticated technologies employed.

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