Smooth Complete Coverage Trajectory Planning Algorithm for a Nonholonomic Robot

Šelek, Ana; Seder, Marija; Brezak, Mišel; Petrović, Ivan

doi:10.3390/s22239269

Cited by 7 publications

(3 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Coverage path planning (CPP) aims to calculate a path covering all points of interest (POIs) to envelop the entire Region of Interest (ROI) [ 19 ]. CPP efficiency and performance are assessed based on coverage, path distance, completion time, energy use, and obstacle avoidance capabilities [ 20 , 21 ]. CPP ties to various autonomous robotics applications like floor cleaning, mowing, agricultural harvesting, demining, and structural inspections [ 22 ].…”

Section: Related Workmentioning

confidence: 99%

Coverage Planning for UVC Irradiation: Robot Surface Disinfection Based on Swarm Intelligence Algorithm

Guo,

Luo,

et al. 2024

Sensors

View full text Add to dashboard Cite

Ultraviolet (UV) radiation has been widely utilized as a disinfection strategy to effectively eliminate various pathogens. The disinfection task achieves complete coverage of object surfaces by planning the motion trajectory of autonomous mobile robots and the UVC irradiation strategy. This introduces an additional layer of complexity to path planning, as every point on the surface of the object must receive a certain dose of irradiation. Nevertheless, the considerable dosage required for virus inactivation often leads to substantial energy consumption and dose redundancy in disinfection tasks, presenting challenges for the implementation of robots in large-scale environments. Optimizing energy consumption of light sources has become a primary concern in disinfection planning, particularly in large-scale settings. Addressing the inefficiencies associated with dosage redundancy, this study proposes a dose coverage planning framework, utilizing MOPSO to solve the multi-objective optimization model for planning UVC dose coverage. Diverging from conventional path planning methodologies, our approach prioritizes the intrinsic characteristics of dose accumulation, integrating a UVC light efficiency factor to mitigate dose redundancy with the aim of reducing energy expenditure and enhancing the efficiency of robotic disinfection. Empirical trials conducted with autonomous disinfecting robots in real-world settings have corroborated the efficacy of this model in deactivating viruses.

show abstract

Section: Related Workmentioning

confidence: 99%

Coverage Planning for UVC Irradiation: Robot Surface Disinfection Based on Swarm Intelligence Algorithm

Guo,

Luo,

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…In [23], a multi-objective cost function was presented that integrated the additional costs of the yaw angle, curvature, reversing, and path length of self-driving agricultural vehicles, which, combined with the heuristic function of Reeds-Shepp curve length, generated a comprehensive priority value, which could ensure the generated paths were continuous and smooth. In [24], an algorithm for generating smooth complete coverage paths is proposed, that utilized clothoid curves, allowing nonholonomic mobile robots to move in optimal time. In [9], the authors presented a method that generated headland turns for parallel tracks with continuous-curvature paths.…”

Section: Related Workmentioning

confidence: 99%

Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints

Höffmann,

Patel,

Büskens

2023

Agriculture

View full text Add to dashboard Cite

Complete coverage path planning (CCPP) is vital in mobile robot applications. Optimizing CCPP is particularly significant in precision agriculture, where it enhances resource utilization, reduces soil compaction, and boosts crop yields. This work offers a comprehensive approach to CCPP for agricultural vehicles with curvature constraints. Our methodology comprises four key stages. First, it decomposes complex agricultural areas into simpler cells, each equipped with guidance tracks, forming a fixed track system. The subsequent route planning and smooth path planning stages compute a path that adheres to path constraints, optimally traverses the cells, and aligns with the track system. We use the generalized traveling salesman problem (GTSP) to determine the optimal traversing sequence. Additionally, we introduce an algorithm for calculating paths that are both smooth and curvature-constrained within individual cells, as well as paths that enable seamless transitions between cells, resulting in a smooth, curvature-constraint coverage path. Our modular approach allows method flexibility at each step. We evaluate our method on real agricultural fields, demonstrating its effectiveness in minimizing path length, ensuring efficient coverage, and adhering to curvature constraints. This work establishes a strong foundation for precise and efficient agricultural coverage path planning, with potential for further real-world applications and enhancements.

show abstract

“…Complete coverage path planning algorithm that generates smooth paths based on clothoids that allow a non-holonomic mobile robot to move in optimal time while following the path is described in [ 12 ]. This algorithm significantly reduces the coverage time, path length and overlap area, and increases the coverage rate compared to state-of-the-art full coverage algorithms.…”

Section: Path Planningmentioning

confidence: 99%