A Novel Docking Algorithm Based On The LiDAR And The V-shape Features

Öz

This paper presents a feature based docking strategy with a LiDAR for a non holonomic mobile platform to be charged at the charging station. The docking station has only a V-shape structure to be detected from the LiDAR scans. The proposed docking algorithm consists of three main sections which are the localization of the V-Shaped feature with the LiDAR measurements, the path generation with a quintic polynomial and the Proportional Integral Derivative (PID) implementation to track the generated points of the path and correct the yaw angle along the way. Once the relative position of the docking station is detected by matching the synthetically generated V-shape feature with the current Lidar scans, the trajectories are generated by calculating the coeeficients of the quintic polynomial. Afterwards, the initial states, the states and the yaw angles at the points along the path are taken as inputs and the algorithm corrects the robot’s yaw angle as it follows the path by a PID control. The algorithm is both tested within the simulation environment and the real test environment. The platform docks with a good accuracy which is around ± 2 cm in x and y, ± 1o in . With the proposed strategy, additional sensors are not necessary on the platform or on the charging station. Moreover, the robot can navigate even in the absence of light with a good accuracy. Hence, a cheaper solution is obtained for an important problem of autonomous mobile robotic applications.

Anahtar Kelimeler

• Non holonomic platform
• Feature based docking
• LiDAR.

V-şekil Özelliklerine ve Lidar Sensörüne Dayalı Yeni Bir Kenetlenme Algoritması

Öz

Bu çalışma, şarj istasyonunda şarj edilecek holonomik olmayan bir mobil platform için LiDAR ile özellik tabanlı bir kenetlenme stratejisi sunar. Şarj/kenetlenme istasyonu, LiDAR taramalarından tespit edilebilecek yalnızca V şeklinde bir yapıya sahiptir. Önerilen yerleştirme algoritması, V-şekil özelliğinin LiDAR ölçümleriyle bulunması, beşli polinom ile yol oluşturulması ve yolun oluşturulan noktalarını izlemek ve düzeltmek için Orantılı İntegral Türev (PID) uygulaması olmak üzere üç ana bölümden oluşur. Sentetik olarak oluşturulan V-şekli özelliği mevcut Lidar taramaları ile eşleştirilerek kenetlenme istasyonunun göreceli konumu tespit edildiğinde, beşli polinomun katsayıları hesaplanarak yörüngeler oluşturulur. Daha sonra, yol boyunca noktalardaki başlangıç durumları, durumlar ve sapma açıları girdi olarak alınır ve algoritma, PID kontrolü ile yolu takip ederken robotun sapma açısını düzeltir. Algoritma hem simülasyon ortamında hem de gerçek test ortamında test edildi. Platform, x ve y'de ± 2 cm, 'de ± 1o civarında olan iyi bir doğrulukla yanaşmaktadır. Önerilen strateji ile platformda veya şarj istasyonunda ek sensörler gerekli değildir. Üstelik robot, ışık olmadığında bile iyi bir doğrulukla hareket edebilir. Böylelikle otonom mobil robotik uygulamalarının önemli bir problemi için daha ucuz bir çözüm elde edilmektedir.

Anahtar Kelimeler

• Holonomik olmayan platform
• Özellik tabanlı kenetlenme
• LiDAR.

Kaynakça

1. Zhang Z., Meng Y., Song B., Meng X. and Li J. (2018). Design and implementation of an automatic charging system for intelligent patrol robot. System Science and Control, vol. 6, no. 3, pp. 19-27, 2018.
2. Won P., Biglarbegian M., and Melek W. (2015). Development of an Effective Docking System for Modular Mobile Self-Configurable Robots Using Extended Kalman Filter and Particle Filter. Robotics, vol. 4, pp. 25-49.
3. Mira Vaz P., Ferreira R., Grossmann V. and Ribeiro M. I. (1997). Docking of a mobile platform based on infrared sensors. IEEE Int. Symposium on Industrial Electronics, July 1997, Guimaraes, Portugal.
4. Song G., Wang H., Zhang J., and Meng T. (2011). Automatic Docking System for Recharging Home Surveillance Robots. IEEE Trans. on Consumer Electronics, vol. 57, no. 2, May.
5. Kim K. H., Choi H.D., Yoon S., Lee K. W., Ryu H.S., Woo C. K., and Kwak Y.K., 2005. Development of Docking System for Mobile Robots Using Cheap Infrared Sensors. 1st Int. Conf. on Sensing Techonology, November, Palmerston North, New Zealand. Testing Automatic Docking. Accessed:2021-02-22, http://wiki.ros.org/kobuki/Tutorials/AutomaticDocking.
6. Kartoun U., Stern H., Edan Y., Feied C., Handler J., Smith M., and Gillam M., (2006). Vision Based Autonomous Robot Self-Docking and Recharging. World Automation Congress, July, Budapest, Hungary.
7. Santos L., Neves dos Santos F., Mendes J., Ferraz N., Lima J., Morais R., and Costa P., (2017). Path Planning for Automatic Recharging System for Steep-Slope Vineyard Robots. ROBOT 2017: Third Iberian Robotics Conference, Advances in Intelligent Systems and computing, vol. 693, Springer.
8. Rosa S., Russo L. O. and Bona B., 2014. Towards a ROS based autonomous cloud robotics platform for data center monitoring. Proceedings of the 2014th IEEE Emerging Technology and Factory Automation, pp. 1-8, Barcelona, Spain. Censi A., 2008. An icp variant using a point-to-line metric. IEEE International Conference on Robotics and Automation, pages 19–25.

9. Rowe C., 2020. Docking Solution for Autonomous Mobile Robots. M.Sc. Thesis, Department of Engineering, Trinity College, Ireland.
10. Sreenivas M. V. And Shivakumar M., 2019. Sensor Guided Docking of Autonomous Mobile Robot for Battery Recharging. Int. Jour. of Recent Technology and Engineering, vol. 8, no. 4.
11. Quilez R., Zeeman A., Mitton N., and Vandaele J., 2015. Docking autonomous robots in passive docks with infrared sensors and QR codes. Int. Conf. on Testbeds and Research Infrastructures for the Development of Networks and Communities, June, Vancouver, Canada.
12. Marostica M., Bullo M., Moro M., Dughiero F., and Menegatti E., 2014. A wireless recharging system for electrical agriculture robots with autonomous docking. Computer Science.
13. Grisetti G., Stachniss C., and Burgard W., 2005. Improving grid-based slam with rao-blackwellized particle filters by adaptive proposals and selective resampling. In Proceedings of the 2005 IEEE International conference on robotics and automation (ICRA), 2432-2437.
14. Özgören M.K., 2020. Kinematics of General Spatial Mechanical Systems. Wiley, 2020.
15. Takahashi A., Hongo T., Ninomiya Y., and Sugimoto G., 1989. Local Path Planning And Motion Control For Agv In Positioning. IEEE/RSJ International Workshop on Intelligent Robots and Systems (IROS '89), The Autonomous Mobile Robots and Its Applications, Tsukuba, Japan, 1989, pp. 392-397.