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Path Planning Aware of Robot’s Center of Mass for Steep Slope Vineyards

Published online by Cambridge University Press:  18 July 2019

Luís Santos*
Affiliation:
CRIIS - Centre for Robotics in Industry and Intelligent Systems, INESC-TEC, Porto, Portugal E-mails: fbnsantos@inesctec.pt, ricardo.g.reis@inesctec.pt, pranjali.shinde@inesctec.pt
Filipe Santos
Affiliation:
CRIIS - Centre for Robotics in Industry and Intelligent Systems, INESC-TEC, Porto, Portugal E-mails: fbnsantos@inesctec.pt, ricardo.g.reis@inesctec.pt, pranjali.shinde@inesctec.pt
Jorge Mendes
Affiliation:
CRIIS - Centre for Robotics in Industry and Intelligent Systems, INESC-TEC, Porto, Portugal E-mails: fbnsantos@inesctec.pt, ricardo.g.reis@inesctec.pt, pranjali.shinde@inesctec.pt UTAD, Vila Real, Portugal. E-mail: jorge.m.mendes@inesctec.pt
Pedro Costa
Affiliation:
CRIIS - Centre for Robotics in Industry and Intelligent Systems, INESC-TEC, Porto, Portugal E-mails: fbnsantos@inesctec.pt, ricardo.g.reis@inesctec.pt, pranjali.shinde@inesctec.pt FEUP, Porto, Portugal. E-mail: pedrogc@fe.up.pt
José Lima
Affiliation:
CRIIS - Centre for Robotics in Industry and Intelligent Systems, INESC-TEC, Porto, Portugal E-mails: fbnsantos@inesctec.pt, ricardo.g.reis@inesctec.pt, pranjali.shinde@inesctec.pt CeDRI and IPB, Bragança, Portugal. E-mail: jllima@ipb.pt
Ricardo Reis
Affiliation:
CRIIS - Centre for Robotics in Industry and Intelligent Systems, INESC-TEC, Porto, Portugal E-mails: fbnsantos@inesctec.pt, ricardo.g.reis@inesctec.pt, pranjali.shinde@inesctec.pt
Pranjali Shinde
Affiliation:
CRIIS - Centre for Robotics in Industry and Intelligent Systems, INESC-TEC, Porto, Portugal E-mails: fbnsantos@inesctec.pt, ricardo.g.reis@inesctec.pt, pranjali.shinde@inesctec.pt
*
*Corresponding author. E-mail: luis.c.santos@inesctec.pt
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Summary

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Steep slope vineyards are a complex scenario for the development of ground robots. Planning a safe robot trajectory is one of the biggest challenges in this scenario, characterized by irregular surfaces and strong slopes (more than 35°). Moving the robot through a pile of stones, spots with high slope or/and with wrong robot yaw may result in an abrupt fall of the robot, damaging the equipment and centenary vines, and sometimes imposing injuries to humans. This paper presents a novel approach for path planning aware of center of mass of the robot for application in sloppy terrains. Agricultural robotic path planning (AgRobPP) is a framework that considers the A* algorithm by expanding inner functions to deal with three main inputs: multi-layer occupation grid map, altitude map and robot’s center of mass. This multi-layer grid map is updated by obstacles taking into account the terrain slope and maximum robot posture. AgRobPP is also extended with algorithms for local trajectory replanning during the execution of a trajectory that is blocked by the presence of an obstacle, always assuring the safety of the re-planned path. AgRobPP has a novel PointCloud translator algorithm called PointCloud to grid map and digital elevation model (PC2GD), which extracts the occupation grid map and digital elevation model from a PointCloud. This can be used in AgRobPP core algorithms and farm management intelligent systems as well. AgRobPP algorithms demonstrate a great performance with the real data acquired from AgRob V16, a robotic platform developed for autonomous navigation in steep slope vineyards.

Type
Articles
Copyright
© Cambridge University Press 2019 

References

Correa, D. S. O., Sciotti, D. F., Prado, M. G., Sales, D. O., Wolf, D. F. and Osorio, F. S., “Mobile Robots Navigation in Indoor Environments Using Kinect Sensor,2012 Second Brazilian Conference on Critical Embedded Systems, Campinas, Brazil (IEEE, 2012) pp. 3641.CrossRefGoogle Scholar
dos Santos, F. B. N., Sobreira, H. M. P., Campos, D. F. B., dos Santos, R. M. P. M., Moreira, A. P. G. M. and Contente, O. M. S., “Towards a Reliable Monitoring Robot for Mountain Vineyards,2015 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Vila Real, Portugal (IEEE, 2015) pp. 3743.CrossRefGoogle Scholar
Rodriguez, S., Tang, X., Lien, J. M. and Amato, N. M. (2006, May). “An Obstacle-Based Rapidly-Exploring Random Tree,Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2006, Orlando, Florida, USA (IEEE) pp. 895900.CrossRefGoogle Scholar
Pivtoraiko, M., Knepper, R. A. and Kelly, A., “Differentially constrained mobile robot motion planning in state lattices,J. Field Rob. 26, 308333 (2009).CrossRefGoogle Scholar
Fernandes, E., Costa, P., Lima, J. and Veiga, G., “Towards an Orientation Enhanced Astar Algorithm for Robotic Navigation,2015 IEEE International Conference on Industrial Technology (ICIT), Seville, Spain (IEEE, 2015) pp. 33203325.CrossRefGoogle Scholar
Ge, S. S. and Cui, Y. J., “Dynamic motion planning for mobile robots using potential field method,Auton. Rob. 13(3), 207222 (2002).CrossRefGoogle Scholar
Karaman, S., Walter, M. R., Perez, A., Frazzoli, E. and Teller, S., “Anytime Motion Planning Using the RRT,2011 IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China (IEEE, 2011) pp. 14781483.CrossRefGoogle Scholar
Song, X., Fan, X., Cao, Z. and Gao, H., “A TC-RRT-Based Path Planning Algorithm for the Nonholonomic Mobile Robots,2017 36th Chinese Control Conference (CCC), Dalian, China (IEEE, 2017) pp. 6638– 6643.CrossRefGoogle Scholar
Cheein, F. Auat, Torres Torriti, M., Hopfenblatt, N. B., Á. Prado, J. and Calabi, D., “Agricultural service unit motion planning under harvesting scheduling and terrain constraints,J. Field Rob. 34(8), 15311542 (2017).CrossRefGoogle Scholar
Wang, C., Meng, L., She, S., Mitchell, I. M., Li, T., Tung, F., Wan, W., M. Q.-H. Meng and C. W. de Silva, “Autonomous Mobile Robot Navigation in Uneven and Unstructured Indoor Environments,2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada (IEEE, 2017) pp. 109116.CrossRefGoogle Scholar
Gajjar, S., Bhadani, J., Dutta, P. and Rastogi, N., “Complete Coverage Path Planning Algorithm for Known 2D Environment,2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), Bengaluru, India (IEEE, 2017) pp. 963967.Google Scholar
Valente, J., Sanz, D., J. Del Cerro, A. Barrientos and M. Á. de Frutos, “Near-optimal coverage trajectories for image mosaicing using a mini quad-rotor over irregular-shaped fields,Precis. Agric. 14(1), 115132 (2013).CrossRefGoogle Scholar
Jin, J. and Tang, L., “Coverage path planning on three dimensional terrain for arable farming,J. Field Rob. 28(3), 424440 (2011).CrossRefGoogle Scholar
Goto, T., Kosaka, T. and Noborio, H., “On the Heuristics of A* or A Algorithm in ITS and Robot Path-Planning,Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003,(IROS 2003), Las Vegas, USA, vol. 2 (IEEE, 2003) pp. 11591166.Google Scholar
Do Nascimento, T. P., Costa, P., Costa, P. G., Moreira, A. P. and Conceição, A. G. S., “A set of novel modifications to improve algorithms from the A* family applied in mobile robotics,J. Braz. Comput. Soc. 19(2), 167179 (2013).CrossRefGoogle Scholar
Moreira, A. P., Costa, P. and Costa, P., “Real-Time Path Planning Using a Modified A* Algorithm,In: Proceedings of ROBOTICA 2009-9th Conference on Mobile Robots and Competitions (2009).Google Scholar
Santos, L., dos Santos, F. N., Mendes, J., Ferraz, N., Lima, J., Morais, R. and Costa, P., “Path Planning for Automatic Recharging System for Steep-Slope Vineyard Robots,Iberian Robotics Conference (Springer, Cham, 2017) (pp. 261272).Google Scholar
Schirmer, R., Biber, P. and Stachniss, C., “Efficient Path Planning in Belief Space for Safe Navigation,2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE, 2017) pp. 2857– 2863.CrossRefGoogle Scholar
Tian, W., “The Research into Methods of Map Building and Path Planning on Mobile Robots,2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chengdu, China (IEEE, 2017) pp. 10871090.CrossRefGoogle Scholar
Stoyanov, T., Magnusson, M., Andreasson, H. and J., A. Lilienthal, “Path Planning in 3D Environments Using the Normal Distributions Transform,2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan (IEEE) pp. 32633268.Google Scholar
Mendes, J. M., dos Santos, F. N., Ferraz, N. A., do Couto, P. M. and dos Santos, R. M., “Localization based on natural features detector for steep slope Vineyards,J. Intell. Rob. Syst. 93(3–4), 433446 (2019).CrossRefGoogle Scholar
Wang, W., Dong, W., Su, Y., Wu, D. and Du, Z., “Development of search and rescue robots for underground coal mine applications,J. Field Rob. 31(3), 386407 (2014).CrossRefGoogle Scholar