Vision-based Waypoints Tracking Control for an Amphibious Spherical Robot

The localization plays an important role in the motion control and trajectory tracking of amphibious spherical robot. However, due to the complex environment in the water, some methods localization on land such as GPS cannot be applied to amphibious spherical robot. Therefore, a new method is needed to locate the amphibious spherical robot. This paper proposes an image recognition method using a global camera to locate the robot. In this method, the global camera is mounted on a platform with a known position, and the computer vision algorithm is used to identify the position of the amphibious spherical robot in the image, then calculate the coordinates and moving speed of the amphibious spherical robot. We applied this method to an amphibious spherical robot and verified it experimentally. In the experiment, the amphibious spherical robot can swim along the set rectangular trajectory by using this localization method, indicating that this localization method is effective.

[1]  Shuxiang Guo,et al.  Visual Detection and Tracking System for a Spherical Amphibious Robot , 2017, Sensors.

[2]  Anahid Bassiri,et al.  Particle Filter and Finite Impulse Response Filter Fusion and Hector SLAM to Improve the Performance of Robot Positioning , 2018, J. Robotics.

[3]  Jen-Fa Huang,et al.  Integrating Correlation Acquisition with Location Optimization for Accurate Indoor Lightwave Robot Positioning , 2017, FNC/MobiSPC.

[4]  Shuxiang Guo,et al.  A system on chip-based real-time tracking system for amphibious spherical robots , 2017 .

[5]  Mamoru Minami,et al.  Visual-servo-based autonomous docking system for underwater vehicle using dual-eyes camera 3D-pose tracking , 2015, 2015 IEEE/SICE International Symposium on System Integration (SII).

[6]  Wei Song,et al.  3-D hand & eye-vergence approaching visual servoing with Lyapunouv-stable pose tracking , 2011, 2011 IEEE International Conference on Robotics and Automation.

[7]  Shuxiang Guo,et al.  The communication and stability evaluation of amphibious spherical robots , 2018 .

[8]  Olivier Gibaru,et al.  Locally optimal control under unknown dynamics with learnt cost function: application to industrial robot positioning , 2017 .

[9]  Shuxiang Guo,et al.  Modal and fatigue analysis of critical components of an amphibious spherical robot , 2017 .

[10]  Hyun Myung,et al.  Localization of AUVs using visual information of underwater structures and artificial landmarks , 2017, Intell. Serv. Robotics.

[11]  Shuxiang Guo,et al.  Motion Characteristic Evaluation of an amphibious spherical robot , 2019, Int. J. Robotics Autom..

[12]  Shuxiang Guo,et al.  Development and evaluation of a Venus flytrap-inspired microrobot , 2016 .

[13]  Shuxiang Guo,et al.  Modeling and experimental evaluation of an improved amphibious robot with compact structure , 2018, Robotics and Computer-Integrated Manufacturing.

[14]  Chyi-Yeu Lin,et al.  Image-Sensor-Based Fast Industrial-Robot Positioning System for Assembly Implementation , 2017 .

[15]  Shu-Li Sun Multi-sensor information fusion white noise filter weighted by scalars based on Kalman predictor , 2004, Autom..

[16]  Shuxiang Guo,et al.  Hybrid Locomotion Evaluation for a Novel Amphibious Spherical Robot , 2018 .

[17]  H. Suzuki,et al.  Visual servoing to catch fish using global/local GA search , 2005, IEEE/ASME Transactions on Mechatronics.

[18]  Shuxiang Guo,et al.  Performance Evaluation of a Novel Propulsion System for the Spherical Underwater Robot (SURIII) , 2017 .

[19]  E. An,et al.  A Robust Fuzzy Autonomous Underwater Vehicle (AUV) Docking Approach for Unknown Current Disturbances , 2012, IEEE Journal of Oceanic Engineering.

[20]  Ana I. Pereira,et al.  A fast and robust kinematic model for a 12 DoF hyper-redundant robot positioning: An optimization proposal , 2017 .

[21]  Haryong Song,et al.  Robust Vision-Based Relative-Localization Approach Using an RGB-Depth Camera and LiDAR Sensor Fusion , 2016, IEEE Transactions on Industrial Electronics.

[22]  Shuxiang Guo,et al.  Underwater motion characteristics evaluation of multi amphibious spherical robots , 2018, Microsystem Technologies.

[23]  Jwu-Sheng Hu,et al.  Design of Sensing System and Anticipative Behavior for Human Following of Mobile Robots , 2014, IEEE Transactions on Industrial Electronics.

[24]  Zhaoxia Fu,et al.  Centroid weighted Kalman filter for visual object tracking , 2012 .

[25]  S. Y. Chen,et al.  Kalman Filter for Robot Vision: A Survey , 2012, IEEE Transactions on Industrial Electronics.

[26]  Shuxiang Guo,et al.  Hydrodynamic Analysis-Based Modeling and Experimental Verification of a New Water-Jet Thruster for an Amphibious Spherical Robot , 2019, Sensors.

[27]  Shuxiang Guo,et al.  A Kinect-Based Real-Time Compressive Tracking Prototype System for Amphibious Spherical Robots , 2015, Sensors.

[28]  L. Huang,et al.  Mobile robot positioning system for precision manufacturing: The laser lighthouse revisited , 2017, 2017 3rd International Conference on Control, Automation and Robotics (ICCAR).