638 research outputs found
Robust Environmental Mapping by Mobile Sensor Networks
Constructing a spatial map of environmental parameters is a crucial step to
preventing hazardous chemical leakages, forest fires, or while estimating a
spatially distributed physical quantities such as terrain elevation. Although
prior methods can do such mapping tasks efficiently via dispatching a group of
autonomous agents, they are unable to ensure satisfactory convergence to the
underlying ground truth distribution in a decentralized manner when any of the
agents fail. Since the types of agents utilized to perform such mapping are
typically inexpensive and prone to failure, this results in poor overall
mapping performance in real-world applications, which can in certain cases
endanger human safety. This paper presents a Bayesian approach for robust
spatial mapping of environmental parameters by deploying a group of mobile
robots capable of ad-hoc communication equipped with short-range sensors in the
presence of hardware failures. Our approach first utilizes a variant of the
Voronoi diagram to partition the region to be mapped into disjoint regions that
are each associated with at least one robot. These robots are then deployed in
a decentralized manner to maximize the likelihood that at least one robot
detects every target in their associated region despite a non-zero probability
of failure. A suite of simulation results is presented to demonstrate the
effectiveness and robustness of the proposed method when compared to existing
techniques.Comment: accepted to icra 201
Sweep coverage of discrete time multi-robot networks with general topologies
summary:This paper addresses a sweep coverage problem of multi-robot networks with general topologies. To deal with environmental uncertainties, we present discrete time sweep coverage algorithms to guarantee the complete coverage of the given region by sweeping in parallel with workload partition. Moreover, the error between actual coverage time and the optimal time is estimated with the aid of continuous time results. Finally, numerical simulation is conducted to verify the theoretical results
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
Distributed navigation of multi-robot systems for sensing coverage
A team of coordinating mobile robots equipped with operation specific sensors can
perform different coverage tasks. If the required number of robots in the team is
very large then a centralized control system becomes a complex strategy. There
are also some areas where centralized communication turns into an issue. So, a
team of mobile robots for coverage tasks should have the ability of decentralized or
distributed decision making. This thesis investigates decentralized control of mobile
robots specifically for coverage problems. A decentralized control strategy is ideally
based on local information and it can offer flexibility in case there is an increment
or decrement in the number of mobile robots. We perform a broad survey of the
existing literature for coverage control problems. There are different approaches
associated with decentralized control strategy for coverage control problems. We
perform a comparative review of these approaches and use the approach based on
simple local coordination rules. These locally computed nearest neighbour rules are
used to develop decentralized control algorithms for coverage control problems.
We investigate this extensively used nearest neighbour rule-based approach for
developing coverage control algorithms. In this approach, a mobile robot gives an
equal importance to every neighbour robot coming under its communication range.
We develop our control approach by making some of the mobile robots playing
a more influential role than other members of the team. We develop the control
algorithm based on nearest neighbour rules with weighted average functions. The
approach based on this control strategy becomes efficient in terms of achieving a
consensus on control inputs, say heading angle, velocity, etc.
The decentralized control of mobile robots can also exhibit a cyclic behaviour
under some physical constraints like a quantized orientation of the mobile robot.
We further investigate the cyclic behaviour appearing due to the quantized control
of mobile robots under some conditions. Our nearest neighbour rule-based approach
offers a biased strategy in case of cyclic behaviour appearing in the team of mobile
robots.
We consider a clustering technique inside the team of mobile robots. Our decentralized
control strategy calculates the similarity measure among the neighbours
of a mobile robot. The team of mobile robots with the similarity measure based
approach becomes efficient in achieving a fast consensus like on heading angle or
velocity. We perform a rigorous mathematical analysis of our developed approach.
We also develop a condition based on relaxed criteria for achieving consensus on
velocity or heading angle of the mobile robots. Our validation approach is based on
mathematical arguments and extensive computer simulations
Collision Free Navigation of a Multi-Robot Team for Intruder Interception
In this report, we propose a decentralised motion control algorithm for the
mobile robots to intercept an intruder entering (k-intercepting) or escaping
(e-intercepting) a protected region. In continuation, we propose a
decentralized navigation strategy (dynamic-intercepting) for a multi-robot team
known as predators to intercept the intruders or in the other words, preys,
from escaping a siege ring which is created by the predators. A necessary and
sufficient condition for the existence of a solution of this problem is
obtained. Furthermore, we propose an intelligent game-based decision-making
algorithm (IGD) for a fleet of mobile robots to maximize the probability of
detection in a bounded region. We prove that the proposed decentralised
cooperative and non-cooperative game-based decision-making algorithm enables
each robot to make the best decision to choose the shortest path with minimum
local information. Then we propose a leader-follower based collision-free
navigation control method for a fleet of mobile robots to traverse an unknown
cluttered environment where is occupied by multiple obstacles to trap a target.
We prove that each individual team member is able to traverse safely in the
region, which is cluttered by many obstacles with any shapes to trap the target
while using the sensors in some indefinite switching points and not
continuously, which leads to saving energy consumption and increasing the
battery life of the robots consequently. And finally, we propose a novel
navigation strategy for a unicycle mobile robot in a cluttered area with moving
obstacles based on virtual field force algorithm. The mathematical proof of the
navigation laws and the computer simulations are provided to confirm the
validity, robustness, and reliability of the proposed methods
Theoretical and Experimental Collaborative Area Coverage Schemes Using Mobile Agents
This chapter is concerned with the development of collaborative control schemes for mobile ground robots for area coverage purposes. The simplest scheme assumes point omnidirectional robots with heterogeneous circular sensing patterns. Using information from their spatial neighbors, each robot (agent) computes its cell relying on the power diagram partitioning. If there is uncertainty in inferring the locations of these robots, the Additively Weighted Guaranteed Voronoi scheme is employed resulting in a rather conservative performance. The aforementioned schemes are enhanced by using a Voronoi-free coverage scheme that relies on the knowledge of any arbitrary sensing pattern employed by the agents. Experimental results are offered to highlight the efficiency of the suggested control laws
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