Table 1 - uploaded by Xiaotian Yang
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Parameter of robot and simulation

Parameter of robot and simulation

Context in source publication

Context 1
... results in Table 1 and corresponding Fig. 11 are the average results of 100 tests for 1 to 7 robots. The row code shows the time for algorithm. ...

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This paper presents the implementation of smart cuckoo search (SCS) algorithm for intelligent path planning of mobile robots. A new fitness function is modeled and optimized by SCS algorithm to generate collision free optimal route for the mobile robots. The simulation results are illustrated to verify the ability of robot to deal with different en...

Citations

... The assumption claims that the length, width (and height if it is a 3D area) of the search area is much larger than the sensing range so that the gaps between the sensed area and the boundary are small enough to be ignored so targets would not appear in those gaps [3]. However, some other papers ignored this assumption but still claimed they reached the complete coverage or a complete search [223,132,131,128,129,130,133,12,10,14,11]. Those papers could only be correct by having assumptions about the shape of the boundary and passage width. ...
... There are various assumptions for the sensing ability of sensors [207]. Most papers [223,132,131,128,129,130,133,12,10,14,11,221,224,221,224] assumed a fixed circular sensing range in 2D tasks and a spherical range in 3D tasks. However, some papers used a directional sensing range especially for some surveillance tasks using cameras [55,101,56,199]. ...
... The distributed algorithm for deployment is designed based on the search algorithm in [223,225,222,221]. The flow chart of the algorithm is in Figure 3.3 and the abbreviation 'comm' in that figure is short for communication. ...
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Decentralized control of robots has attracted huge research interests. However, some of the research used unrealistic assumptions without collision avoidance. This report focuses on the collision-free control for multiple robots in both complete coverage and search tasks in 2D and 3D areas which are arbitrary unknown. All algorithms are decentralized as robots have limited abilities and they are mathematically proved. The report starts with the grid selection in the two tasks. Grid patterns simplify the representation of the area and robots only need to move straightly between neighbor vertices. For the 100% complete 2D coverage, the equilateral triangular grid is proposed. For the complete coverage ignoring the boundary effect, the grid with the fewest vertices is calculated in every situation for both 2D and 3D areas. The second part is for the complete coverage in 2D and 3D areas. A decentralized collision-free algorithm with the above selected grid is presented driving robots to sections which are furthest from the reference point. The area can be static or expanding, and the algorithm is simulated in MATLAB. Thirdly, three grid-based decentralized random algorithms with collision avoidance are provided to search targets in 2D or 3D areas. The number of targets can be known or unknown. In the first algorithm, robots choose vacant neighbors randomly with priorities on unvisited ones while the second one adds the repulsive force to disperse robots if they are close. In the third algorithm, if surrounded by visited vertices, the robot will use the breadth-first search algorithm to go to one of the nearest unvisited vertices via the grid. The second search algorithm is verified on Pioneer 3-DX robots. The general way to generate the formula to estimate the search time is demonstrated. Algorithms are compared with five other algorithms in MATLAB to show their effectiveness.
... [5,6]. In the proposed algorithm, temporary local networks are employed as in [7][8][9]. ...
... In decentralize search algorithms, some publications using grids had rigorous proofs of the convergence of their algorithms [7,8,13] but they may not prove 100% coverage. Although [9] proved 100% blanket coverage, it required robots to exceed the boundaries, which limits the range of * This work was supported by the Australian Research Council. ...
... [7,9,13] only proved that robots can go through every vertex of the grid but their authors directly thought that proof is equal to the proof of 100% coverage. Actually, part of the area is not detected which was discussed in [8]. However, [8] only considered the area in passages without considering the area near boundaries. ...
... Current algorithms for coverage related problems were usually for 2D environments [8][9][10] which had a relatively easy geographical feature and can be applied to the plane ground and the surface of the water. Several pieces of literature researched the problem in 3D area such as [11,12] thus can be used in the flight in a 3D terrain and the underwater exploration. ...
... Several pieces of literature researched the problem in 3D area such as [11,12] thus can be used in the flight in a 3D terrain and the underwater exploration. Inspired by the search for MH370 in the underwater environment, this paper improved the 2D algorithm in [8] and modified it to apply to a 3D area. ...
... [15,16]. In the proposed algorithm, temporary local networks are employed for data communication when robots are staying at vertices as in [8,17,18]. ...