3 research outputs found
Decentralized Autonomous Navigation Strategies for Multi-Robot Search and Rescue
In this report, we try to improve the performance of existing approaches for
search operations in multi-robot context. We propose three novel algorithms
that are using a triangular grid pattern, i.e., robots certainly go through the
vertices of a triangular grid during the search procedure. The main advantage
of using a triangular grid pattern is that it is asymptotically optimal in
terms of the minimum number of robots required for the complete coverage of an
arbitrary bounded area. We use a new topological map which is made and shared
by robots during the search operation. We consider an area that is unknown to
the robots a priori with an arbitrary shape, containing some obstacles. Unlike
many current heuristic algorithms, we give mathematically proofs of convergence
of the algorithms. The computer simulation results for the proposed algorithms
are presented using a simulator of real robots and environment. We evaluate the
performance of the algorithms via experiments with real robots. We compare the
performance of our own algorithms with three existing algorithms from other
researchers. The results demonstrate the merits of our proposed solution. A
further study on formation building with obstacle avoidance for a team of
mobile robots is presented in this report. We propose a decentralized formation
building with obstacle avoidance algorithm for a group of mobile robots to move
in a defined geometric configuration. Furthermore, we consider a more
complicated formation problem with a group of anonymous robots; these robots
are not aware of their position in the final configuration and need to reach a
consensus during the formation process. We propose a randomized algorithm for
the anonymous robots that achieves the convergence to a desired configuration
with probability 1. We also propose a novel obstacle avoidance rule, used in
the formation building algorithm.Comment: arXiv admin note: substantial text overlap with arXiv:1402.5188 by
other author
Decentralized Collision-Free Control of Multiple Robots in 2D and 3D Spaces
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