Conference PaperPDF Available

Distributed control of a robotic network for protection of a region from intruders

December 2017

DOI:10.1109/ROBIO.2017.8324516

Conference: 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)

Project: Multi Robot Navigation Control

Authors:

Andrey V Savkin

UNSW Sydney

Ali Marzoughi

Engineering Institute of Technology

The region R, the boundary segment S and the curvilinear coordinate c(P ).

…

Figures - uploaded by Ali Marzoughi

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Content uploaded by Ali Marzoughi

Content may be subject to copyright.

Distributed Control of a Robotic Network for

Protection of a Region from Intruders⇤

Andrey V. Savkin,1Ali Marzoughi,2

Abstract—This paper addresses a problem of intruder inter-

ception on the boundary of a protected region through the use of

a network of mobile robots. A necessary and sufﬁcient condition

for the existence of a solution of this problem is obtained. We

propose a decentralized motion control algorithm for the mobile

robots to intercept an intruder entering the protected region.

The algorithm is developed based on some simple rules that are

computationally efﬁcient and easily implementable in real time.

I. Introduction

The important recent technological developments in robotics

greatly increase the number of real world applications that

are suitable for multi-robot teams. Therefore, in recent years,

the use of teams of autonomous unmanned vehicles in pa-

trolling, monitoring and surveillance tasks has been increased

signiﬁcantly. A fundamental problem of robotics research is

navigation of mobile robots for patrolling a boundary of a

region in various border-security missions; see e.g. [1]–[10].

The most common approach to protection a region from

intruders is coverage control in which the barrier coverage

problem and the sweep coverage problem are studied. The

barrier coverage problem is to deploy a group of mobile robots

with sensing capabilities to form a static sensor barrier that

detects any object trying to enter a protected region [11],

[12]. On the other hand, the sweep coverage problem is to

steer a group of mobile robots along the boundary of the

protected region so that every point in some neighbourhood

of the boundary is detected by some robot [13], [14].

In this paper, we consider a team of mobile robots moving

along the boundary of a protected planar region. The robots

move in a decentralized fashion, i.e. each robot navigates

independently and has information about current coordinates

of just several closest other robots. Unlike coverage control

problems of [11]–[14], we assume that the intruder becomes

visible to the robots at some time , i.e. all the robots know

the planar coordinates of the intruder after a certain time

moment. The objective of the multi-robot team is to intercept

the intruder which means that when the interceptor crosses

the boundary of the protected region, there should be several

robots close to the interception point. The proposed problem

statement is relevant to various problems of asset guarding

in which a team of autonomous unmanned surface vehicles

*This work was supported by the Australian Research Council.

1.A.V.Savkin is with the School of Electrical Engineering,and Telecom-

munications, The University of New South Wales, Sydney 2052, Australia,

e-mail: a.savkin@unsw.edu.au.

2.A.Marzoughi is with the School of Electrical Engineering,and Telecom-

munications, The University of New South Wales, Sydney 2052, Australia,e-

mail: a.marzoughi@student.unsw.edu.au

(USVs) patrols and guards an asset in an environment with

hostile boats. Such problems require the team of USVs to co-

operatively patrol the area around the asset, identify intruders,

and actively block them [15]–[17]. An important example is

safeguarding civilian harbours from terrorist attacks coming

from the blue border (i.e. the sea-side) [18].

In this paper, we give a necessary and sufﬁcient condition

for existence of decentralized navigation strategy for the multi-

robot team that always results in intercepting the intruder

and proposed such a strategy. The proposed decentralized

navigation law is computationally non-demanding and easily

implementable in real time. Mathematically rigorous proofs of

the main theoretical results of the paper will be given in its

extended journal version.

The remainder of the paper is organized as follows. Section

II. states the problem under investigation. The main results are

presented in Section III.. Examples illustrating the proposed

navigation strategy are given in Section IV.. Finally, Section

V. presents a brief conclusion.

II. Problem Statement

Let Rbe a bounded closed connected and linearly con-

nected planar region with a piecewise smooth boundary. Fur-

thermore, let Sbe a segment of the boundary of the region

Rbetween some points P1and P2; see Fig.(1). We consider

a moving point-wise intruder Ithat aims to enter the region

Rthrough the segment Sfrom outside of R; see Fig.(1).

Let xI(t)be planar coordinates of the intruder. The intruder

is moving in the plane with an arbitrary time-varying vector

velocity vI(t)= ˙xI(t)satisfying the constraint

kvI(t)kVmax

I8t0(1)

where Vmax

I>0is a given constant, k·kdenotes the

standard Euclidean vector norm. Also, xI(t)denotes the planar

coordinates of the intruder.

Moreover, let nbe a given positive integer. We consider

nmobile point-wise robots labelled 1,2,...,n that defend

the region Rfrom the intruder. Unlike the intruder that can

move in any direction in the plane, the robots can move

only along the segment Sin the both directions. Furthermore,

x1(t),x

2(t),...,x

n(t)denote the planar coordinates of the

robots 1,2,...,n.

We introduce the curvilinear coordinate c(P)for any point

P2Ssuch that c(P)is the length of the portion of the

segment Sbetween the points P1and P; see Fig.(1). This

implies that c(P1)=0and c(P2)=Lwhere Lis the length

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Fig. 1. The region R, the boundary segment Sand the curvilinear coordinate

c(P).

of the segment S. We assume that c1(t):=c(x1(t)),c

2(t):=

c(x2(t)),...,c

n(t):=c(xn(t)) are the curvilinear coordinates

of the robots 1,2,...,n at time t0.

Furthermore, we suppose that the robots labelled according

to their curvilinear coordinates so that

0c1(t)c2(t)...cn(t)L8t0.(2)

The requirement (2) means that the robots never change their

order on the segment S. We assume that the motion of the

robots along Sis described by the equation

˙ci(t)=ui(t)8k=1,2,...,n (3)

where ui(t)is the control input of the robot i. We assume that

the control inputs ui(t)satisfy the constraint

|ui(t)|Vmax

R8t0(4)

where Vmax

R>0is a given constant.

Available measurements: Let 1k<n

2be a given

positive integer. At any time t, each robot iknows the

curvilinear coordinates cj(t)of the robots jfor all ik

ji+k. Moreover, the robot knows its own coordinate

ci(t). Furthermore, the intruder becomes visible to the robots

at some time t00, i.e. all the robots know the planar

coordinates xI(t)of the intruder for all tt0.

Deﬁnition 1: Let ✏>0be a given constant. Suppose that

the intruder crosses the segment Sat time t?, i.e. xI(t?)2S.

We say that the multi-robot team kintercepts the intruder

at time t?if there exists some index i=1,2,...,n such

that |c(xI(t?)) cj(t?)|✏for all iji+k1.

Furthermore, a multi-robot team navigation strategy that is

based on the available information is called kintercepting

if for any movement of the intruder, the multi-robot team

kintercepts it when the intruder crosses the segment S.

In other words, kintercept means that when the interceptor

crosses the segment S, there should be at least krobots close

to the interception point.

Problem statement: The intruder’s objective is to enter the

region Rthrough the segment Swhile avoiding kintercept

by the multi-robot team. The objective of the multi-robot team

is to kintercept the intruder. The problem under considera-

tion in this paper is to derive a necessary and sufﬁcient con-

dition under which kintercept is possible for any motion of

the intruder, and design a decentralized navigation strategy for

the multi-robot team that is based on the available information

and will always result in kintercept of the intruder.

III. The Main Results

Let P2Sand xbe a point outside the region R. Then

P(x, P )denotes the set of all continuous piecewise smooth

paths L(x, P )connecting xand Psuch that the intersection

of L(x, P )and Rcontains only the point P. Furthermore,

let ↵(x, P )denote the inﬁmum of the lengths of all paths

L(x, P )from P(x, P ). Moreover, let i(1),i(2),...,i(n)be a

permutation of indices 1,2,...,n such that

|ci(1)(t)c(P)||ci(2) (t)c(P)|···|ci(n)(t)c(P)|.

Then, introduce the variable (t, P ):=|ci(k)(t)c(P)|.

In other words, (t, P )is the kth among all the robots

according to the length of the sub-segments of the segment

Sbetween the robots’ current locations and the point P.

Introduce the function F(s)from the interval [0,L]to the

segment Ssuch that for any number s2[0,L],F(s)is the

point P2Ssuch that c(P)=s. Furthermore, let [A1,A

denote the closed sub-segment of the segment Sbetween the

points A1and A2. For i=k, k +1,...,nk+1, introduce

sub-segments Si(t),S

i(t)+of the segment Sas follows:

Si(t):= [F(ci(t)+cik(t)

2),F(ci(t)+cik+1(t)

2)]

if i =k+1,...,nk+ 1;

Si(t):= [P1,F(ci(t)+cik+1(t)

2)]

if i =k;

Si(t)+:= [F(ci(t)+ci+k1(t)

2),F(ci(t)+ci+k(t)

2)]

if i =k, . . . , n k;

Si(t)+:= [F(ci(t)+ci+k1(t)

2),P

if i =nk+1.(5)

Moreover, for i=k,k +1,...,nk+1, introduce the numbers

M

i(t)and M+

i(t)as

M

i(t):= sup

P2Si(t)✓(t, P )↵(xI(t),P)Vmax

Vmax

I◆;

M+

i(t):= sup

P2Si(t)+✓(t, P )↵(xI(t),P)Vmax

Vmax

I◆.(6)

Now we can introduce the following decentralized navigation

law:

ui(t):=Vmax

Rif i < k

ui(t):=Vmax

Rif i > n k+1 (7)

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For i=k, k +1,...,nk+1,

ui(t):=Vmax

Rif M

i(t)<M

i(t)

ui(t):=Vmax

Rif M

i(t)>M

i(t)

ui(t):=0 if M

i(t)=M+

i(t).(8)

Remark 1: The intuition behind the decentralized navi-

gation law can be explained as follows. The sub-segments

Si(t),S

i(t)+are sets of point of the curve Sfor which the

robot iis the kth furthest robot at time t. The robot moves

with the maximum allowed speed towards the one of these

segments that is more ”dangerous” at the current time, i.e. it

has the biggest possible distance between the intruder and the

kth robot at the moment of crossing Sby the intruder. This

biggest possible distance is described by (6).

We will also need the following assumption.

Assumption 1: For any trajectory [xI(t),c

1(t),...,c

n(t)] of

the intruder-multi-robot team system, there exists no more than

ﬁnite number of time instants ⌧such that M

i(⌧)=M+

i(⌧).

Theorem 1: Consider the multi-robot team (3) and the

intruder satisfying (1), (4) and Assumption 1. Let 1k<n

be a given positive integer. Then there exists a kintercepting

multi-robot team navigation strategy if and only if

sup

P2S✓(t0,P)↵(xI(t0),P)Vmax

Vmax

I◆✏(9)

where t00is the time at which the intruder becomes visible

to the robots. Moreover, if the inequality (9) holds, then the

navigation law (7), (8) is a kintercepting navigation strategy.

The proof of Theorem 1 will be given in the full version of

the paper.

The inequality (9) and the navigation law (7), (8) can be

made computationally simpler under the following assump-

tion.

Assumption 2: The following inequality holds:

Vmax

IVmax

For i=k, k +1,...,n k+1, introduce points

Di(t),D

i(t)+of the segment Sas follows:

Di(t):= F(ci(t)+cik(t)

2)(10)

if i =k+1,...,nk+ 1;

Di(t):= P1if i =k;

Di(t)+:= F(ci(t)+ci+k(t)

2)(11)

if i =k,...,nk;

Di(t)+:= P2if i =nk+1.(12)

Moreover, for i=k,k +1,...,nk+1, introduce the numbers

H

i(t)and H+

i(t)as follows:

H

i(t):=ci(t)cik(t)

2↵(xI(t),D

i(t))Vmax

Vmax

if i =k+1,...,nk+ 1;

H

i(t):=ci(t)↵(xI(t),P

1)Vmax

Vmax

if i =k;

H+

i(t):=ci+k(t)ci(t)

2↵(xI(t),D

i(t)+)Vmax

Vmax

if i =k,...,nk;

H+

i(t):=Lci(t)↵(xI(t),P

1)Vmax

Vmax

if i =nk+1.(13)

For i<kand i>nk, the navigation law (7) stays the

same. For i=k, k+1,...,nk+1, the simpliﬁed navigation

law (7) becomes:

ui(t):=Vmax

Rif H

i(t)<H

i(t)

ui(t):=Vmax

Rif H

i(t)>H

i(t)

ui(t):=0 if H

i(t)=H+

i(t).(14)

Also, we modify Assumption 1 as follows.

Assumption 3: For any trajectory [xI(t),c

1(t),...,c

n(t)] of

the intruder-multi-robot team system, there exists no more than

ﬁnite number of time instants ⌧such that H

i(⌧)=H+

i(⌧).

Theorem 2: Consider the multi-robot team (3) and the in-

truder satisfying (1), (4) and Assumptions 2, 3. Let 1k<n

be a given positive integer. Furthermore, let Hbe the set of

numbers H

i(t0),H+

i(t0)where i=k, k +1,...,nk+1

and t00is the time at which the intruder becomes visible

to the robots. Then there exists a kintercepting multi-robot

team navigation strategy if and only if

max H✏.(15)

Moreover, if the inequality (15) holds, then the navigation law

(7), (14) is a kintercepting navigation strategy.

The proof of Theorem 2 will be given in the full version of

the paper.

IV. Illustrative Examples

In this section, we consider a team of ﬁve mobile robots

deployed on the boundary of a planar region to intercept

the intruder that aims to enter this region. Our illustrative

examples include the problems of kintercepting the intruder

by the multi-robot team with k=1and k=2. In our

examples, Vmax

I=4.2and Vmax

R=3.0, hence, Assumption

2 holds. Therefore, we apply Theorem 2 and the navigation

law (7), (14). Fig. (2) illustrates the reaction of the robots to

the intruder’s motion when it starts moving from the initial

position ithrough the trajectory to the points a,b, and c

where k=1. Similarly, Fig. (3) represents the trajectory of

the intruder and the robots’ position when k=2.

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(a) (b)

Fig. 2. The intruder trajectory and the positions of the robots when the

intruder at points i,a,b and c, k=1.

(a) (b)

Fig. 3. The intruder trajectory and the positions of the robots when the

intruder at points i,a,b and c, k=2.

Fig.(4a) shows the evolution of the ycoordinates of the

intruder and the robots during the trajectory shown in Fig.(2)

with k=1. Analogously, Fig.(4b) shows the evolution of

the ycoordinates of the intruder and the robots during the

trajectory shown in Fig.(3) with k=2.

V. Conclusion

We proposed a decentralized motion control algorithm for

a network of mobile robots to intercept an intruder on the

boundary of a protected planar region. A necessary and

sufﬁcient condition for the existence of such an algorithm was

derived. The proposed algorithm is based on some simple rules

that only require information about the closest neighbours of

(a)

(b)

Fig. 4. The evolution of the ycoordinates of the intruder and the robots for

k=1and k=2.

each robot and the intruder. Computer simulations conﬁrmed

the efﬁciency of the developed navigation algorithm.

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Collision Free Navigation of a MultiRobot Team for Intruder Interception

Technical Report

Full-text available

Sep 2018

Ali Marzoughi

The ability of mobile robots to work as a team in hard and hazardous environments and consequently their widespread use in various industries is a strong incentive for researchers to develop practical algorithm and methods for increasing the performance of mobile robots. The ability of autonomous decision-making for navigation and path planning is the important problem, which has been investigated by researchers to improve the performance of a team of mobile robots in a certain mission. The contribution of this study is classified as follows; In the first stage, 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 continue, 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. At the second stage, 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. Third, we propose a leader-follower based collision-free navigation control method for a fleet of mobile robots to traverse an unknown cluttered environment. Fourth, we propose a decentralised navigation algorithm for a team of multi-robot to traverse an area where occupied by multiple obstacles to trap a target. We prove that each individual team 3 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. 4

Collision Free Navigation of a Multi-Robot Team for Intruder Interception

Preprint

Full-text available

Sep 2018

Ali Marzoughi

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.

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We study problems of intercepting single and multiple invasive intruders on a boundary of a planar region by employing a team of autonomous unmanned surface vehicles. First, the problem of intercepting a single intruder has been studied and then the proposed strategy has been applied to intercepting multiple intruders on the region boundary. Based on the proposed decentralised motion control algorithm and decision making strategy, each autonomous vehicle intercepts any intruder, which tends to leave the region by detecting the most vulnerable point of the boundary. An efficient and simple mathematical rules based control algorithm for navigating the autonomous vehicles on the boundary of the see region is developed. The proposed algorithm is computationally simple and easily implementable in real life intruder interception applications. In this paper, we obtain necessary and sufficient conditions for the existence of a real-time solution to the considered problem of intruder interception. The effectiveness of the proposed method is confirmed by computer simulations with both single and multiple intruders.

Decentralized decision making and navigation strategy for tracking intruders in a cluttered area by a group of mobile robots

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Jun 2020

Muhammad Usman Arif

In the current era of the industrial revolution, mobile robots are playing a pivotal role in helping out mankind in many complex and hazardous environments for performing tasks like search and rescue, obstacle avoidance, mining and security surveillance, etc. A lot of navigation algorithms have been developed in recent years but novel challenges still exist in autonomous path planning of multiple robots to track and follow multiple intruders. This report demonstrates a decentralized strategy of arithmetic mean based navigation algorithm for a group of mobile robots to navigate through an unknown environment filled with obstacles to detect and follow multiple invading intruders. The suggested navigation strategy ensures that mobile robots safely move right in the middle of surrounding obstacles to maintain a safe distance and to avoid collision with obstacles and each other. The conventional method of color recognition is used to detect dynamic intruders and calculate pixel values using the Microsoft Kinect sensor camera. A probability of danger algorithm is introduced to ensure that all the intruders present in the environment are being followed by friendly robots on the bases of the minimum distance between an intruder and its follower. The mobile robots follow intruders movement on the bases of their pixel values. The low pixel value means that intruder is far away and high pixel value represents that intruder is closer to the friendly robots. All the algorithms and image processing techniques are implemented and tested in WEBOTS simulation environment using C programming language and the results show the success of proposed arithmetic mean based navigation and probability of danger based intruders following algorithms.

Optimal Feedback Strategy of a Superior Evader Passing Between Two Pursuers

Conference Paper

Oct 2020

Arithmetic mean-based decision-making algorithm for obstacle avoidance and multiple intruder detection

Conference Paper

Nov 2020

Data driven hybrid edge computing-based hierarchical task guidance for efficient maritime escorting with multiple unmanned surface vehicles

Article

Full-text available

Sep 2020

The advancement of hardware and software technology makes multiple cooperative unmanned surface vehicles (USVs) utilized in maritime escorting with low cost and high efficiency. USVs can work as edge computing devices to locally and cooperatively perform heavy computational tasks without dependence of remote cloud servers. As such, we organize a team of USVs to escort a high value ship (e.g., mother ship) in a complex maritime environment with hostile intruder ships, where the significant challenge is to learn cooperation of USVs and assign each USV tasks to achieve optimal performance. To this end, in this paper, a hierarchical scheme is proposed for the USV team to guard a valuable ship, which belongs to problems of sparse rewards and long-time horizons in multi-agent reinforcement learning. The core idea utilized in the proposed scheme is centralized training with decentralized execution, where USVs learn policies to guard a high-value ship with extra shared environmental data from other USVs through communication. Specifically, the ships are divided into two groups, i.e., high-level ship and low-level USVs. The high-level ship optimizes decision-level policy to predict intercept points, while each low-level USV utilizes multi-agent reinforcement learning to learn task-level policy to intercept intruders. The hierarchical task guidance is exploited in maritime escorting, whereby high-level ship’s decision-level policy guides the training and execution of task-level policies of USVs. Simulation results and experiment analysis show that the proposed hierarchical scheme can efficiently execute the escort mission.

Cooperative Robots to Observe Moving Targets: Review

Article

Full-text available

Dec 2016

The deployment of multiple robots for achieving a common goal helps to improve the performance, efficiency, and/or robustness in a variety of tasks. In particular, the observation of moving targets is an important multirobot application that still exhibits numerous open challenges, including the effective coordination of the robots. This paper reviews control techniques for cooperative mobile robots monitoring multiple targets. The simultaneous movement of robots and targets makes this problem particularly interesting, and our review systematically addresses this cooperative multirobot problem for the first time. We classify and critically discuss the control techniques: cooperative multirobot observation of multiple moving targets, cooperative search, acquisition, and track, cooperative tracking, and multirobot pursuit evasion. We also identify the five major elements that characterize this problem, namely, the coordination method, the environment, the target, the robot and its sensor(s). These elements are used to systematically analyze the control techniques. The majority of the studied work is based on simulation and laboratory studies, which may not accurately reflect real-world operational conditions. Importantly, while our systematic analysis is focused on multitarget observation, our proposed classification is useful also for related multirobot applications.

Protecting Assets within a Civilian Harbour through the Use of a Team of USVs: Interception of Possible Menaces

Conference Paper

Full-text available

Jan 2010

The protection of civilian harbours has received an increasing interest after September 11th. One of the areas currently under major investigation is the use of a team of Unmanned Surface Vehicles (USVs), which could be exploited for patrolling purposes and to investigate suspect situations, increasing the effectiveness of the harbor protection system while lowering the number of humans directly exposed to threats. To achieve such aims, the USVs must be properly coordinated by an intelligent Swarm Management Unit (SMU), whose realization is the goal of an on-going research project carried out by the authors' organizations. This paper presents the latest results of the SMU project, i.e. a menace interception system, that off-line optimizes the positioning of the USV team and on-line selects the most suitable USV for intercepting any possible menace.

Maximizing the probability of intrusion detection by a fleet of mobile robots using an intelligent game theoretic approach

Conference Paper

Sep 2017

Ali Marzoughi

This paper presents an intelligent game based decision-making algorithm (IGD) for a fleet of mobile robots to maximize the probability of detection in a limited area. The agents have the minimum communication or even no communication result from a jamming attack by a given hostile. Thus, we proved that the proposed diagonal initial formation results in optimal barrier coverage. Based on our decentralized cooperative non-cooperative game based algorithm, each robot can individually make the best decision to choose the shortest path with minimum local information. Therefore, each agent consumes minimum energy result from using less memory in addition to maximizing the probability of detection, which leads to achieving maximum payoff individually, and in the interest of the group.

A navigation strategy for an autonomous patrol vehicle based on multi-fusion planning algorithms and multi-paradigm representation schemes

Article

Aug 2017
ROBOT AUTON SYST

This paper considers the robot navigation task as an algorithmic and representational one in a way that the performance of the navigation task cannot be measured without combining those two elements. As a result of this view, a unique new navigation strategy based on combined multi-fusion planning algorithms and multi-paradigm representation schemes is presented. An overall architecture for a new navigation strategy is also proposed. Discrete and continuous planning algorithms are combined in a hierarchal fashion. GIS models and ontology are also combined to form rich media for representing dynamic data and knowledge. Experimental results with an evaluation of the schemes are presented.

Self-deployment of mobile robotic networks: an algorithm for decentralized sweep boundary coverage

Article

Aug 2016

SUMMARY Several non-holonomic Dubins-car-like robots travel over paths with bounded curvatures in a plane that contains an a priori unknown region. The robots are anonymous to one another and do not use communication facilities. Any of them has access to the current minimum distance to the region and can determine the relative positions and orientations of the other robots within a finite and given visibility range. We present a distributed navigation and guidance strategy under which every robot autonomously converges to the desired minimum distance to the region with always respecting a given safety margin, the robots do not collide with one another and do not get into clusters, and the entire team ultimately sweeps over the respective equidistant curve at a speed exceeding a given threshold, thus forming a kind of a sweeping barrier at the perimeter of the region. Moreover, this strategy provides effective sub-uniform distribution of the robots over the equidistant curve. Mathematically rigorous justification of the proposed strategy is offered; its effectiveness is confirmed by extensive computer simulations and experiments with real wheeled robots.

Distributed Coordination Control for Multi-Robot Networks Using Lyapunov-Like Barrier Functions

Article

Jan 2015
IEEE T AUTOMAT CONTR

This paper addresses the problem of multi-agent coordination and control under multiple objectives, and presents a set-theoretic formulation amenable to Lyapunov-based analysis and control design. A novel class of Lyapunov-like barrier functions is introduced and used to encode multiple, non-trivial control objectives, such as collision avoidance, proximity maintenance and convergence to desired destinations. The construction is based on recentered barrier functions and on maximum approximation functions. Thus, a single Lyapunov-like function is used to encode the constrained set of each agent, yielding simple, gradient-based control solutions. The derived control strategies are distributed, i.e., based on information locally available to each agent, which is dictated by sensing and communication limitations. Furthermore, the proposed coordination protocol dictates semi-cooperative conflict resolution among agents, which can be also thought as prioritization, as well as conflict resolution with respect to an agent (the leader) which is not actively participating in collision avoidance, except when necessary. The considered scenario is pertinent to surveillance tasks and involves nonholonomic vehicles. The efficacy of the approach is demonstrated through simulation results.

Decentralized Coverage Control Problems For Mobile Robotic Sensor and Actuator Networks

Book

May 2015

This book introduces various coverage control problems for mobile sensor networks including barrier, sweep and blanket. Unlike many existing algorithms, all of the robotic sensor and actuator motion algorithms developed in the book are fully decentralized or distributed, computationally efficient, easily implementable in engineering practice and based only on information on the closest neighbours of each mobile sensor and actuator and local information about the environment. Moreover, the mobile robotic sensors have no prior information about the environment in which they operation. These various types of coverage problems have never been covered before by a single book in a systematic way. Another topic of this book is the study of mobile robotic sensor and actuator networks. Many modern engineering applications include the use of sensor and actuator networks to provide efficient and effective monitoring and control of industrial and environmental processes. Such mobile sensor and actuator networks are able to achieve improved performance and efficient monitoring together with reduction in power consumption and production cost. © 2015 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

Model-predictive asset guarding by team of autonomous surface vehicles in environment with civilian boats

Article

Mar 2014

In this paper, we present a contract-based, decentralized planning approach for a team of autonomous unmanned surface vehicles (USV) to patrol and guard an asset in an environment with hostile boats and civilian traffic. The USVs in the team have to cooperatively deal with the uncertainty about which boats pose an actual threat and distribute themselves around the asset to optimize their guarding opportunities. The developed planner incorporates a contract-based algorithm for allocating tasks to the USVs through forward simulating the mission and assigning estimated utilities to candidate task allocation plans. The task allocation process uses a form of marginal cost-based contracting that allows decentralized, cooperative task negotiation among neighboring agents. The task allocation plans are realized through a corresponding set of low-level behaviors. In this paper, we demonstrate the planner using two mission scenarios. However, the planner is general enough to be used for a variety of scenarios with mission-specific tasks and behaviors. We provide detailed analysis of simulation results and discuss the impact of communication interruptions, unreliable sensor data, and simulation inaccuracies on the performance of the planner.

Algorithms for collision-free navigation of mobile robots in complex cluttered environments: A survey

Article

Mar 2014

We review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given certain assumptions about the system). This topic continues to be an active area of research, and we highlight some directions in which available approaches may be improved. The paper discusses models of the sensors and vehicle kinematics, assumptions about the environment, and performance criteria. Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are all reviewed. In preference to global approaches based on full knowledge of the environment, particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.

Model-predictive target defense by team of unmanned surface vehicles operating in uncertain environments

Conference Paper

May 2013

In this paper, we present a heuristic planning approach for guarding a valuable asset by a team of autonomous unmanned surface vehicles (USVs) operating in a continuous state-action space. The team's objective is to maximize the amount of time it takes an intruder boat to reach the asset. The team must cooperatively deal with uncertainty about which boats are actual intruders, employ active blocking to slow down intruders' movement towards the asset, and intelligently distribute themselves around the target to optimize future guarding opportunities. Our planner incorporates a market-based algorithm for allocating tasks to individual USVs by forward-simulating the mission and assigning estimated utilities to candidate task-allocation plans. The planner can be automatically adapted to a specific mission by optimizing the behaviors used to fulfil individual tasks. We present detailed simulation results that demonstrate the effectiveness of our approach.