Sensor-Based Coverage for Demining: Exact Cellular Decompositions and Uncertain Detectors

Author(s):  
Howie Choset ◽  
Ercan U. Acar ◽  
Yangang Zhang ◽  
Mark Schervish

Abstract Coverage path planning is the determination of a path that a robot must take in order to pass itself, a detector, or some other effector over each point in an environment. Applications include demining, floor scrubbing, and inspection. In previous work, we developed the boustrophedon cellular decomposition, an exact cellular decomposition approach, for the purposes of coverage. Each cell in the boustrophedon decomposition is covered with simple back and forth motions. Therefore, coverage is reduced to finding an exhaustive path through a graph that represents the adjacency relationships of the cells in the boustrophedon decomposition. Such a path will ensure that a detector passes over all points in the environment, but it does not guarantee that all ordnance is indeed detected because mine detectors have error. Therefore, we also consider probabilistic methods to determine paths for the robot to maximize the likelihood of detecting all ordnance in a target location using a priori known information.

Author(s):  
Prithviraj Dasgupta

The multi-robot coverage path-planning problem involves finding collision-free paths for a set of robots so that they can completely cover the surface of an environment. This problem is non-trivial as the geometry and location of obstacles in the environment is usually not known a priori by the robots, and they have to adapt their coverage path as they discover obstacles while moving in the environment. Additionally, the robots have to avoid repeated coverage of the same region by each other to reduce the coverage time and energy expended. This chapter discusses the research results in developing multi-robot coverage path planning techniques using mini-robots that are coordinated to move in formation. The authors present theoretical and experimental results of the proposed approach using e-puck mini-robots. Finally, they discuss some preliminary results to lay the foundation of future research for improved coverage path planning using coalition game-based, structured, robot team reconfiguration techniques.


Mechatronics ◽  
2011 ◽  
Vol 21 (5) ◽  
pp. 876-885 ◽  
Author(s):  
Yan Li ◽  
Hai Chen ◽  
Meng Joo Er ◽  
Xinmin Wang

2020 ◽  
Author(s):  
Qile He ◽  
Yu Sun

Many robot applications depend on solving the Complete Coverage Path Problem (CCPP). Specifically, robot vacuum cleaners have seen increased use in recent years, and some models offer room mapping capability using sensors such as LiDAR. With the addition of room mapping, applied robotic cleaning has begun to transition from random walk and heuristic path planning into an environment-aware approach. In this paper, a novel solution for pathfinding and navigation of indoor robot cleaners is proposed. The proposed solution plans a path from a priori cellular decomposition of the work environment. The planned path achieves complete coverage on the map and reduces duplicate coverage. The solution is implemented inside the ROS framework, and is validated with Gazebo simulation. Metrics to evaluate the performance of the proposed algorithm seek to evaluate the efficiency by speed, duplicate coverage and distance travelled.


Robotica ◽  
2020 ◽  
pp. 1-22
Author(s):  
K. R. Guruprasad ◽  
T. D. Ranjitha

SUMMARY A new coverage path planning (CPP) algorithm, namely cell permeability-based coverage (CPC) algorithm, is proposed in this paper. Unlike the most CPP algorithms using approximate cellular decomposition, the proposed algorithm achieves exact coverage with lower coverage overlap compared to that with the existing algorithms. Apart from a formal analysis of the algorithm, the performance of the proposed algorithm is compared with two representative approximate cellular decomposition-based coverage algorithms reported in the literature. Results of demonstrative experiments on a TurtleBot mobile robot within the robot operating system/Gazebo environment and on a Fire Bird V robot are also provided.


Author(s):  
Zeba Khanam ◽  
Sangeet Saha ◽  
Dimitri Ognibene ◽  
Klaus McDonald-Maier ◽  
Shoaib Ehsan

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 4 ◽  
Author(s):  
Tauã Cabreira ◽  
Lisane Brisolara ◽  
Paulo R. Ferreira Jr.

Coverage path planning consists of finding the route which covers every point of a certain area of interest. In recent times, Unmanned Aerial Vehicles (UAVs) have been employed in several application domains involving terrain coverage, such as surveillance, smart farming, photogrammetry, disaster management, civil security, and wildfire tracking, among others. This paper aims to explore and analyze the existing studies in the literature related to the different approaches employed in coverage path planning problems, especially those using UAVs. We address simple geometric flight patterns and more complex grid-based solutions considering full and partial information about the area of interest. The surveyed coverage approaches are classified according to a classical taxonomy, such as no decomposition, exact cellular decomposition, and approximate cellular decomposition. This review also contemplates different shapes of the area of interest, such as rectangular, concave and convex polygons. The performance metrics usually applied to evaluate the success of the coverage missions are also presented.


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