Squircular-CPP: A Smooth Coverage Path Planning Algorithm based on Squircular Fitting and Spiral Path
Authors: 
Mahdi Hassan, Dikai Liu, Xiang ChenAuthors Info & Claims
Mahdi Hassan, Dikai Liu, Xiang ChenAuthors Info & ClaimsPages 1075 - 1081
Abstract
Coverage path planning (CPP) is essential for applications such as robotic floor cleaning and high-pressure cleaning of surfaces. Smooth CPP algorithms have several benefits including smoother motion of the robot and the reduction of aggressive accelerations and decelerations resulting from sharp turns. In this paper, a novel smooth CPP algorithm is presented which is named Squircular-CPP. This algorithm proposes a squircular shape, which is an intermediate shape between the circle and the square, to fit a target area. Squircular-CPP can also fit a shape between the ellipse and the rectangle. The shape fitting is simple, fast, and analytical and doesn’t require a preselection of the shape (i.e., square, circle, ellipse or rectangle). It enables and complements the creation of a smooth spiral path within the fitted shape. Several case studies are presented to demonstrate the effectiveness of the algorithm and to compare it against the popular boustrophedon-based coverage approach and the Deformable Spiral CPP (DSCPP) algorithm.
References
[1]
M. Hassan and D. Liu, “Simultaneous area partitioning and allocation for complete coverage by multiple autonomous industrial robots,” Autonomous Robots, vol. 41, no. 8, pp. 1609–1628, Dec 2017.
[2]
R. Almadhoun, T. Taha, L. Seneviratne, J. Dias, and G. Cai, “A survey on inspecting structures using robotic systems,” International Journal of Advanced Robotic Systems, vol. 13, no. 6, pp. 1–18, Dec 2016.
[3]
A. Khan, I. Noreen, and Z. Habib, “On complete coverage path planning algorithms for non-holonomic mobile robots: Survey and challenges.” Journal of Information Science & Engineering, vol. 33, no. 1, pp. 101–121, Jan 2017.
[4]
Y. Mei, Y.-H. Lu, Y. C. Hu, and C. S. G. Lee, “Energy-efficient motion planning for mobile robots,” in IEEE International Conference on Robotics and Automation, vol. 5, April 2004, pp. 4344–4349.
[5]
T.-K. Lee, S.-H. Baek, Y.-H. Choi, and S.-Y. Oh, “Smooth coverage path planning and control of mobile robots based on high-resolution grid map representation,” Robotics and Autonomous Systems, vol. 59, no. 10, pp. 801–812, 2011.
[6]
Y. H. Choi, T. K. Lee, S. H. Baek, and S. Y. Oh, “Online complete coverage path planning for mobile robots based on linked spiral paths using constrained inverse distance transform,” in International Conference on Intelligent Robots and Systems, 2009, pp. 5788–5793.
[7]
M. Hassan and D. Liu, “A deformable spiral based algorithm to smooth coverage path planning for marine growth removal,” in International Conference on Intelligent Robots and Systems, 2018, pp. 1913–1918.
[8]
J. Woolfrey, D. Liu, and M. Carmichael, “Kinematic control of an autonomous underwater vehicle-manipulator system (AUVMS) using autoregressive prediction of vehicle motion and model predictive control,” in International Conference on Robotics and Automation (ICRA), May 2016, pp. 4591–4596.
[9]
T. K. Lee, S. H. Baek, S. Y. Oh, and Y. H. Choi, “Complete coverage algorithm based on linked smooth spiral paths for mobile robots,” in International Conference on Control Automation Robotics Vision, Dec 2010, pp. 609–614.
[10]
F. Balampanis, I. Maza, and A. Ollero, “Spiral-like coverage path planning for multiple heterogeneous UAS operating in coastal regions,” in International Conference on Unmanned Aircraft Systems, June 2017, pp. 617–624.
[11]
J. Backman, P. Piirainen, and T. Oksanen, “Smooth turning path generation for agricultural vehicles in headlands,” Biosystems Engineering, vol. 139, pp. 76–86, 2015.
[12]
E. Gonzalez, P. Aristizabal, and M. Alarcon, “Backtracking spiral algorithm: a mobile robot region filling strategy,” in International Symposium on Robotics and Automation, 2002, pp. 261–266.
[13]
E. Gonzalez, O. Alvarez, Y. Diaz, C. Parra, and C. Bustacara, “BSA: A complete coverage algorithm,” in IEEE International Conference on Robotics and Automation, April 2005, pp. 2040–2044.
[14]
E. Galceran and M. Carreras, “A survey on coverage path planning for robotics,” Robotics and Autonomous Systems, vol. 61, no. 12, pp. 1258–1276, 2013.
[15]
Z. Ren, J. Yuan, and W. Liu, “Minimum near-convex shape decomposition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 10, pp. 2546–2552, Oct 2013.
[16]
S. Asafi, A. Goren, and D. Cohen-Or, “Weak convex decomposition by lines-of-sight,” Computer Graphics Forum, vol. 32, no. 5, pp. 23–31, 2013.
[17]
D. Chaudhuri and A. Samal, “A simple method for fitting of bounding rectangle to closed regions,” Pattern Recognition, vol. 40, no. 7, pp. 1981–1989, 2007.
[18]
C. Fong, “Analytical methods for squaring the disc,” arXiv preprint arXiv:1509.06344, 2015.
[19]
C. Yoo, R. Fitch, and S. Sukkarieh, “Online task planning and control for fuel-constrained aerial robots in wind fields,” The International Journal of Robotics Research, vol. 35, no. 5, pp. 438–453, 2016.
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Jul 2020
1638 pages
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IEEE Press
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Published: 06 July 2020
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