A novel solution with rapid Voronoi-based coverage path planning in irregular environment for robotic mowing systems

Abstract

This paper presents a novel solution of coverage path planning for robotic mowing applications. The planning algorithm is based on the Boustrophedon motions and the rapid Voronoi diagram. The coordinate conversion and the sweeping vector is defined by minimum bounding box and the Voronoi travel paths are designed to reduce the computational cost and execution time compared to conventional heuristic methods. The tracked path is controlled via dynamic feedback in standard lawn mowing robots under robot operating system (ROS). Within ROS, the information exchanging among different tasks of both extensive simulation cases and experimental field tests can be conducted easily. When meeting unknown obstacles, the proposed algorithm can re-plan its paths dynamically. The performance of the proposed algorithm is compared to several conventional coverage algorithms in terms of time efficiency, coverage, repetition, and robustness with respect to both concave and convex shapes. The field tests are conducted to demonstrate that the applicability of the sensor fusion and robustness of the proposed algorithm for the complete coverage tasks by robotic mowers.

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

“…In [78], an efficient coverage path planning algorithm based on Boustrophedon motions and rapid Voronoi diagram is presented, demonstrating superior time efficiency and coverage compared to conventional heuristic methods. In manipulator robot applications, [79] provides an in-depth review of fuzzy logic approaches for collision-free path planning, highlighting their efficiency and applicability in complex and cluttered workspace. For unmanned aerial vehicle surveying missions, an optimal edge-vertex back-and-forth path planner is proposed in [80,81], considering starting and ending points, thus providing an efficient solution for coverage path planning.…”

Emerging Trends in Realistic Robotic Simulations: A Comprehensive Systematic Literature Review

“…• Lawn mowing in irregular environments. [131] obstacles are static, deterministic algorithms such as Dijkstra's algorithm [119], [120], [151] and A* [71], [156]- [158] are often employed. Their reliability and predictability make them suitable for tasks where deviations from a set path can be costly.…”

“…AMARL 29 [162], VFH+ 30 [76], SND 31 [76], A-FGM 32 [85], CNN [163], [164] 4 -Navigation CNN + MGRL 33 [165], RL + APPL 34 [53], DWA [166], BDI 35 [79], [123], ANN 36 + DPP 37 [24], B-spline curves [82], Petri Nets [111], PID 38 controller + RANSAC 39 [117], DRL [37], PaCcET [72], AMCL 41 [167]- [172], Control Mechanisms 1 -Motion Control RBFNN 42 [115], ANN [173], Fuzzy inference [174], DDPG [51], Kalman Filters [86], B-RV [131], TD3 44 [26], Evolutionary algorithm [35]…”

“…Reference Numbers Gazebo Simulators Gazebo only [13], [15], [18], [22], [28], [30], [33], [35], [36], [53], [78], [84]- [88], [90], [92]- [96], [98], [102], [104]- [107], [111], [112], [115], [116], [123], [125], [131], [137], [140], [143], [144], [147], [150], [151], [155], [156], [158], [159], [162], [166], [178], [181], [188], [192], [193], [195], [197], [199]-[202] Gazebo + RViz [1],…”

“…The application of AI in navigation, harvesting, and disaster management [106], [107], [115], [118]- [120] illuminates a technological response to complex real-world challenges. Additionally, the emergence of WMRs in unconventional sectors like "Entertainment" and "Household" [129], [131] offers a glimpse into the future where the boundary between conventional industrial applications and everyday life becomes increasingly blurred.…”