Leader-Follower Formation Control of Nonholonomic Mobile Robots with Input Constraints

Similar documents
Leader follower formation control of nonholonomic mobile robots with input constraints

Sliding mode formation tracking control of a tractor and trailer - car system

Leader-Follower Formation Control and Visibility Maintenance of Nonholonomic Mobile Robots

Coordinated Path Following for Mobile Robots

Formation Control of Nonholonomic Mobile Robots

Vision-based range estimation via Immersion and Invariance for robot formation control

EXPERIMENTAL ANALYSIS OF COLLECTIVE CIRCULAR MOTION FOR MULTI-VEHICLE SYSTEMS. N. Ceccarelli, M. Di Marco, A. Garulli, A.

Non-Collision Conditions in Multi-agent Robots Formation using Local Potential Functions

Observer design via Immersion and Invariance for vision-based leader-follower formation control

Dynamic region following formation control for a swarm of robots

A Switching Active Sensing Strategy to Maintain Observability for Vision-Based Formation Control

Leader-Follower Formation Control and Visibility Maintenance of Nonholonomic Mobile Robots. Fabio Morbidi. Tesi di Dottorato

OVER the past few years, multi-agent systems and cooperative

On the stability of nonholonomic multi-vehicle formation

Adaptive Leader-Follower Formation Control of Autonomous Marine Vehicles

Formation Control of Mobile Robots with Obstacle Avoidance using Fuzzy Artificial Potential Field

An Evaluation of UAV Path Following Algorithms

Cooperative Target Capturing with Multiple Heterogeneous Vehicles

Necessary and Sufficient Graphical Conditions for Formation Control of Unicycles

Target Localization and Circumnavigation Using Bearing Measurements in 2D

Introduction to Dynamic Path Inversion

Experimental validation of a decentralized control law for multi-vehicle collective motion

Trajectory tracking & Path-following control

An homotopy method for exact tracking of nonlinear nonminimum phase systems: the example of the spherical inverted pendulum

Stabilizing a Multi-Agent System to an Equilateral Polygon Formation

Decentralized Formation Control and Connectivity Maintenance of Multi-Agent Systems using Navigation Functions

Consensus Based Formation Control Strategies for Multi-vehicle Systems

Formation path following control of unicycle-type mobile robots

Formation Stabilization of Multiple Agents Using Decentralized Navigation Functions

Nonlinear Formation Control of Marine Craft

On the Controllability of Nearest Neighbor Interconnections

Using Orientation Agreement to Achieve Planar Rigid Formation

On visibility maintenance via controlled invariance for leader-follower Dubins-like vehicles

Target Tracking via a Circular Formation of Unicycles

Nonlinear Tracking Control of Underactuated Surface Vessel

MULTI-AGENT TRACKING OF A HIGH-DIMENSIONAL ACTIVE LEADER WITH SWITCHING TOPOLOGY

arxiv: v2 [cs.ro] 9 May 2017

Consensus Algorithms are Input-to-State Stable

Nonholonomic Constraints Examples

Formation Control of Multi Agent System in Cyclic Pursuit with Varying Inter-Agent Distance

Complex Laplacians and Applications in Multi-Agent Systems

Cooperative visibility maintenance for leader-follower formations in obstacle environments

A Control Lyapunov Function Approach to Multiagent Coordination

Cooperative Control of Unmanned Vehicles in a Time-Varying Flowfield

Robot Control Basics CS 685

VSP 2001/04/20 Prn:27/01/2006; 8:31 {RA} F:ar2385.tex; VTeX/VJ p. 1 (50-131)

Decentralized Stabilization of Heterogeneous Linear Multi-Agent Systems

Sliding mode control for coordination in multi agent systems with directed communication graphs

DSCC TIME-OPTIMAL TRAJECTORIES FOR STEERED AGENT WITH CONSTRAINTS ON SPEED AND TURNING RATE

A Graph-Theoretic Characterization of Controllability for Multi-agent Systems

Event-based Motion Coordination of Multiple Underwater Vehicles Under Disturbances

Vision-based Control Laws for Distributed Flocking of Nonholonomic Agents

Consistent Triangulation for Mobile Robot Localization Using Discontinuous Angular Measurements

Three-Dimensional Motion Coordination in a Time-Invariant Flowfield

Decentralized Cooperative Conflict Resolution Among Multiple Autonomous Mobile Agents

Coordinated Path Following Control of Multiple Wheeled Robots with Directed Communication Links

Discontinuous Backstepping for Stabilization of Nonholonomic Mobile Robots

Global stabilization of an underactuated autonomous underwater vehicle via logic-based switching 1

This is the published version of a paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

Observer design for a general class of triangular systems

Formation Control for Underactuated Autonomous Underwater Vehicles Using the Approach Angle

NONLINEAR PATH CONTROL FOR A DIFFERENTIAL DRIVE MOBILE ROBOT

Distributed Receding Horizon Control of Cost Coupled Systems

Cooperative Control Synthesis for Moving-Target-Enclosing with Changing Topologies

Scaling the Size of a Multiagent Formation via Distributed Feedback

Available online at ScienceDirect. IFAC PapersOnLine 50-1 (2017)

Distributed Structural Stabilization and Tracking for Formations of Dynamic Multi-Agents

Smooth Path Generation Based on Bézier Curves for Autonomous Vehicles

Three-Dimensional Motion Coordination in a Spatiotemporal Flowfield

Tracking a mobile target by multi-robot circumnavigation using bearing measurements

Towards Decentralization of Multi-robot Navigation Functions

Curve Tracking Control for Autonomous Vehicles with Rigidly Mounted Range Sensors

Agreement Problems in Networks with Directed Graphs and Switching Topology

ARTIFICIAL POTENTIAL FIELDS FOR TRAILER-LIKE SYSTEMS 1. T.A. Vidal-Calleja,2 M. Velasco-Villa E. Aranda-Bricaire,3

Linear Algebra and its Applications

Extremal Trajectories for Bounded Velocity Differential Drive Robots

Cooperative formation control of underactuated marine vehicles for target surveillance under sensing and communication constraints

arxiv: v1 [cs.sy] 10 Feb 2017

A motion planner for nonholonomic mobile robots

Generating Patterns with a Unicycle

Towards Abstraction and Control for Large Groups of Robots

Control of Mobile Robots Prof. Luca Bascetta

Tracking control for multi-agent consensus with an active leader and variable topology

Extremal Trajectories for Bounded Velocity Mobile Robots

Globally Stable Adaptive Formation Control of Euler-Lagrange Agents via Potential Functions

Localización Dinámica de Robots Móviles Basada en Filtrado de Kalman y Triangulación

Distributed Game Strategy Design with Application to Multi-Agent Formation Control

Multi-agent gradient climbing via extremum seeking control

Stability Analysis of One-Dimensional Asynchronous Swarms

Collective Motion of Ring-Coupled Planar Particles

Tracking control strategy for the standard N-trailer mobile robot geometrically motivated approach

Observability Analysis of 3D AUV Trimming Trajectories in the Presence of Ocean Currents using Single Beacon Navigation

Maintaining visibility for leader-follower formations in obstacle environments

Localization and Circumnavigation of a Slowly Moving Target Using Bearing Measurements

CONTROL OF THE NONHOLONOMIC INTEGRATOR

Experimental Implementation of Flocking Algorithms in Wheeled Mobile Robots

EE Mobile Robots

Non-holonomic constraint example A unicycle

Real-time trajectory generation technique for dynamic soaring UAVs

Transcription:

Leader-Follower Formation Control of Nonholonomic Mobile Robots with Input Constraints Luca Consolini a, Fabio Morbidi b, Domenico Prattichizzo b, Mario Tosques c a Dept. of Information Engineering, University of Parma, Via Usberti 181/a, 43100 Parma, Italy b Dept. of Information Engineering, University of Siena, Via Roma 56, 53100 Siena, Italy c Dept. of Civil Engineering, University of Parma, Via Usberti 181/a, 43100 Parma, Italy Abstract The paper deals with leader-follower formations of nonholonomic mobile robots, introducing a formation control strategy alternative to those existing in the literature. Robots control inputs are forced to satisfy suitable constraints that restrict the set of leader possible paths and admissible positions of the follower with respect to the leader. A peculiar characteristic of the proposed strategy is that the follower position is not rigidly fixed with respect to the leader but varies in proper circle arcs centered in the leader reference frame. Key words: Formation control; Autonomous mobile robots; Input constraints; Geometric conditions; Adaptive stabilization 1 Introduction In the last decade formation control became one of the leading research areas in mobile robotics. By formation control we simply mean the problem of controlling the relative position and orientation of the robots in a group while allowing the group to move as a whole. Different robot formation typologies have been studied in the literature: ground vehicles (Das et al., 00; Fax and Murray, 004; Marshall et al., 004; Lin et al., 005; Ghabcheloo et al., 006), unmanned aerial vehicles (UAVs) (Singh et al., 000; Koo and Shahruz, 001), aircraft (Giulietti et al., 000; Fierro et al., 001), surface and underwater autonomous vehicles (AUVs) (Skjetne et al., 00; Edwards et al., 004). Three main approaches have been proposed to tackle the robot formation control problem: behavior based, virtual structure and leader following. In the behavior based approach (Balch and Arkin, 1998; Lawton et al., 003) several desired behaviors (e.g. collision avoidance, formation keeping, target seeking) are pre- This paper was not presented at any IFAC meeting. Corresponding author. Tel.: 39 051 906114; Fax: 39 051 90573. Email addresses: luca.consolini@polirone.mn.it (Luca Consolini), morbidi@dii.unisi.it (Fabio Morbidi), prattichizzo@dii.unisi.it (Domenico Prattichizzo), mario.tosques@unipr.it (Mario Tosques). scribed for each robot. The resulting action of each robot is derived by weighing the relative importance of each behavior. The main problem of this approach is that the mathematical formalization is difficult and consequently it is not easy to guarantee the convergence of the formation to a desired configuration. The virtual structure approach (Lewis and Tan, 1997; Do and Pan, 007) considers the formation as a single virtual rigid structure so that the behavior of the robotic system is similar to that of a physical object. Desired trajectories are not assigned to each single robot but to the entire formation as a whole. The behavior of the formation in this case is exactly predictable but a large inter-robot communication bandwidth is required. In the leader-follower approach a robot of the formation, designed as the leader, moves along a predefined trajectory while the other robots, the followers, are to maintain a desired distance and orientation to the leader (Das et al., 00). Perhaps the main criticism to the leader-follower approach is that it depends heavily on the leader for achieving the goal and over-reliance on a single agent in the formation may be undesirable, especially in adverse conditions (Fax and Murray, 004). Nevertheless leader-follower architectures are particularly appreciated for their simplicity and scalability. The leader-follower formation control of nonholonomic mobile robots with bounded control inputs is the subject of this paper.

We propose a leader-follower setup alternative to those existing in the literature (Mariottini et al., 007), assuming that the desired angle between the leader and the follower is measured in the follower frame instead of the leader frame. As shown in (Consolini et al., 006), this approach guarantees lower control effort and smoother trajectories for the follower than the usual leader-follower approaches defined on the leader reference frame (Das et al., 00). According to the proposed setup we find suitable conditions on leader velocity and trajectory curvature ensuring the follower gets into and keeps the formation while satisfying its own velocity constraints. As pointed out in Remark 1, from a geometric point of view the follower position is not fixed with respect to the leader reference frame but varies in suitable circle arcs centered in the leader reference frame. The main contributions of this paper are stated in two theorems. A first theorem gives a sufficient and necessary condition on leader and follower velocity bounds for the existence of a control law that allows the follower to maintain the formation independently from the trajectory of the leader. A second theorem provides a sufficient condition and a control law for the follower to asymptotically reach the formation for any initial condition and any leader motion, while still respecting the bounds. Notation. The following notation is used in the paper: R = {t R t 0}; a, b R, a b = min{a, b}, a b = max{a, b}; t > 0, sign(t) = 1; sign (0) = 0; t < 0, sign(t) = 1; x, y R n (n 1), x, y = n i=1 x i y i, x = x, x ; θ R, τ(θ) = (cosθ, sinθ) T, ν(θ) = ( sinθ, cosθ) T ; x R \{0}, arg(x) = θ where θ [0, π) and x = x τ(θ); w R, w = w ν(arg(w)). Basic definitions Consider the following definition of robot as a velocity controlled unicycle model. Definition 1 Let R = (x, y, θ) T C 1 ([0, ), R 3 ). R is called a robot with initial condition R R 3 (and control (v, ω) T C 0 ([0, ), R )) if the following system is verified { ẋ = v cosθ, ẏ = v sin θ, θ = ω (x(0), y(0), θ(0)) = R. (1) If v(t) 0, we set κ(t) = ω(t)/v(t) which is the (scalar) curvature of the path followed by the robot at time t. Denote by P(t) = (x(t), y(t)) T the position of R at time t, θ(t) its heading, τ(θ(t)) the normalized velocity vector and ν(θ(t)) the normalized vector orthogonal to τ(θ(t)); then {τ(θ(t)), ν(θ(t))} represents the robot reference frame at time t. d φ R 1 P 1 θ 1 τ(θ 1) P 0 Fig. 1. (d, φ)-formation. R 0 τ(θ 0) Definition Let (V, K, K ) R 3 and R be a robot. We say that R satisfies the trajectory constraint (V, K, K ) if t 0 0 < v(t) V, K κ(t) K. All along the paper we suppose that the following condition is satisfied: Assumption 1 (Physical constraint) Let V p, Kp, K p be three constants. We suppose that every robot considered in this paper satisfies the trajectory constraint (V p, Kp, K p ). This constraint is assumed to be the mechanical limitation common to all the robots considered in this paper. The following definition introduces the notion of leaderfollower formation used in the paper. Definition 3 Let d > 0, φ : φ < π and let R 0 = (P T 0, θ 0 ) T, R 1 = (P T 1, θ 1 ) T be two robots. We say that R 0 and R 1 are in (d, φ)-formation with leader R 0 at time t, if P 0 (t) = P 1 (t) dτ(θ 1 (t) φ), () and, simply, that R 0 and R 1 are in (d, φ)-formation with leader R 0, if () holds for all t 0. Moreover we say that R 0 and R 1 are asymptotically in (d, φ)-formation with leader R 0 if lim P 0(t) (P 1 (t) dτ(θ 1 (t) φ)) = 0. t With reference to Fig. 1, Definition 3 states that two robots R 0, R 1 are in (d, φ)-formation with leader R 0 if the position P 1 of the follower R 1 is always at distance d from the position P 0 of the leader R 0 and the angle between vectors τ(θ 1 ) and P 0 P 1 is constantly equal to φ, that is the position P 0 of the leader remains fixed with respect to the follower reference frame {τ(θ 1 ), ν(θ 1 )}. An equivalent way to state Definition 3 is the following: set the error vector, E(t) = P 0 (t) (P 1 (t) dτ(θ 1 (t) φ)), (3) θ 0

then R 0 and R 1 are in (d, φ)-formation (asymptotically) if and only if E(t) = 0, t 0 (respectively, E(t) = 0). lim t δ φ 3 Characterization of a necessary and sufficient condition for the leader-follower formation d P 0 θ 0 R 0 Problem 1 Set d > 0, φ : φ < π. Let R 0 be a robot satisfying the trajectory constraint (V 0, K 0, K 0 ) and R 1 be another robot. Find necessary and sufficient conditions on V 0, K 0, K 0 such that there exist controls v 1, ω 1 and suitable initial conditions for R 1 such that R 0 and R 1 are in (d, φ)-formation with leader R 0 (remark that v 1 and ω 1 must be such that Assumption 1 is satisfied). R 1 P 1 A d (δ,σ 1, σ ) φ σ 1 σ The following theorem gives an answer to Problem 1. Theorem 1 Set d > 0, φ : φ < π. 1) The following properties are equivalent: A) For any robot R 0 = (P T 0, θ 0 ) T with initial condition R 0, satisfying the trajectory constraint (V 0, K 0, K 0 ), there exists an initial condition R 1 and controls v 1, ω 1 for the robot R 1 = (P T 1, θ 1 ) T such that R 0 and R 1 are in (d, φ)-formation with leader R 0. B) The following properties hold: 1 d K 0 K 0 1 d, if φ 0 1 d K 0 K 0 1 d, if φ < 0 (4) K 0 K 0 K 0 K 0 (5) V 0 cos ( 0 (arcsin(k 0 d cosφ) φ) (φ arcsin(k0 d cosφ))) V p cosφ (6) where K ± 0 = (sign K± p )( ((K ± p ) 1 d sin φ) d cos φ ) 1. (7) ) If B) holds, for any robot R 0 satisfying the trajectory constraint (V 0, K0, K 0 ) and for any robot R 1 which is in (d, φ)-formation at time t = 0 and arcsin(k0 d cosφ) θ 0 (0) θ 1 (0) arcsin(k 0 d cosφ), with controls, v 1 = v 0(t) cos(θ0 θ1 φ), ω 1 = v 0(t) sin(θ0 θ1) d then R 0 and R 1 are in (d, φ)-formation and t 0, (8) arcsin(k 0 d ) θ 0(t) θ 1(t) arcsin(k 0 d ). (9) Fig.. The arc of circle A d ( δ, σ1, σ ). Remark 1 Property (9) shows the connection between the relative heading angle θ 0 θ 1, the curvature of the path followed by the leader R 0, the distance d and the visual angle φ. Moreover this implies the following geometric property. Since robots R 0, R 1 are in (d, φ)-formation, P 0 (t) P 1 (t) = dτ(θ 1 (t) φ) = dτ((θ 0 (t) φ) (θ 1 (t) θ 0 (t))), therefore, defining, for any σ 1 σ, A d (δ(t), σ 1, σ ) = dτ([δ(t) σ 1, δ(t) σ ]) as the arc of circle centered in the origin, radius d, angle of the reference axis δ(t) and aperture (σ σ 1 ), by (9), P 0 (t) P 1 (t) A d (θ 0 (t)φ, arcsin(k 0 d cosφ), arcsin(k 0 d cosφ)) that is P 1 (t) P 0 (t) A d ( θ0 (t) φ π, arcsin(k 0 d cosφ), arcsin(k 0 d cosφ)). ( see Fig. where σ1 = arcsin(k 0 d cosφ), σ = arcsin(k0 d cosφ) and δ(t) = θ 0(t)φπ, in the case K0 < 0 < ) K 0. This shows that, differently from (Das et al., 00), the followers are not rigidly disposed with respect to the leader reference frame, but their relative positions vary in time in suitable circle arcs and only these remain stable with respect to the leader reference frame PROOF. A) B). Suppose that R 0 and R 1 are in (d, φ)-formation, the trajectory constraint 0 < v 0 (t) V 0, K0 κ 0(t) K 0, t 0 (10) is verified and (by Assumption 1) the physical constraint 0 < v 1 (t) V p, K p κ 1 (t) K p, t 0 (11) holds for robot R 1. Since E(t) = P 0 (t) (P 1 (t) dτ(θ 1 (t) φ)) = 0, differentiating it, we get that P 0 = P 1 d θ 1 ν(θ 1 φ), that is v 0 τ(θ 0 ) = v 1 τ(θ 1 ) 3

dω 1 ν(θ 1 φ) which implies, multiplying by the rotation matrix R( θ 1 ) = (τ( θ 1 ), ν( θ 1 )), that v 0 τ(θ 0 θ 1 ) = v 1 (1, 0) T dω 1 ν(φ). Therefore it has to be sin(θ 0 θ 1 ) ω 1 = v 0, (1) d cosφ [ v 1 = v 0 cos(θ 0 θ 1 ) sin(θ ] 0 θ 1 )sinφ cos(θ 0 θ 1 φ) = v 0. (13) Then (8) is true and θ 0 (t) θ 1 (t) < π/, t 0, (14) since v 1 has to be greater than zero by (11). Furthermore, setting β(t) = θ 0 (t) θ 1 (t), on [0, ) β = ω 0 ω 1 = v 0 ( κ0 d cosφ sin β ). (15) d cosφ Let β C 1 ([0, ), R) be a solution of (15), then it is easy to verify that the following properties hold: a) if κ 0 (t)d cosφ c > 1, t 0 then lim t β(t) = ; b) let K be a constant such that K d cosφ 1 if t 0, κ 0 (t) = K < 0 (> 0) and π β(0) π, ( π β(0) π, respectively), then lim t β(t) = arcsin(kd cosφ); c) if 1 d K 0 K 0 1 d, arcsin(k 0 d ) (<)β(0) (<)arcsin(k 0 d cosφ), then arcsin(k 0 d cosφ) (<)β(t) (<)arcsin(k 0 d cosφ), t 0, where the notation (<) means that the property holds also when all inequalities are replaced with <. To verify (4) suppose that φ > 0 (the reasoning is analogous for φ 0). By contradiction, suppose that (4) is false, then at least one of the following two inequalities must be true: K 0 1 > d, K 0 < 1 d. Suppose that K 0 1 > d, and that R 0 follows a circle of curvature K 0 with constant velocity V 0. Then hypothesis a) holds and lim t β(t) =, therefore β is unbounded which is impossible by (14). Suppose that K0 < 1 d, if φ is such that K 0 d cosφ < 1, then, by a) as before, a contradiction follows; suppose that K0 d cosφ 1, since π β(0) π, being β(0) φ < π by (14) and 0 < φ < π we get that lim t β(t) = arcsin(k0 d cosφ), by property b) applied with K = K0 < 0. Therefore lim t v 1 (t) = V 0 ( 1 (K0 d cosφ) K0 d sinφ), which implies lim t v 1 (t) < 0, since K0 < 0 and 1 < (K0 d) which contradicts (11), therefore (4) holds. Suppose now that (5) does not hold, for instance that K 0 > K 0 = sign K p. (16) ((K p ) 1 d sin φ) d cos φ Suppose for example that K 0 K 0 0 (the reasoning for the other case is analogous), then (16) implies that K p < { (K 0 ) d cos φ d sin φ } 1. Suppose that R 0 follows a circle of curvature K 0 with constant velocity V 0. Then by the necessity hypothesis there exist initial conditions such that R 0 and R 1 are in (d, φ)-formation and it has to be lim t sin β(t) = K 0 d cosφ, since β is such that β = V0 d (K 0 d cosφ sin β) and K 0 d cosφ 1, by (4). ω Therefore, by (8): lim t κ 1 (t) = lim 1(t) t v 1(t) = lim t sin β(t) ( d(cos β(t)cosφ sin β(t)sin φ) ) 1 ( 1 = lim t d sign β(t) 1 sin β(t) 1 cosφ sin φ)) 1 = { (K 0 ) d cos φ d sin φ } 1 > K p which is impossible by (11). By contradiction suppose that (6) is false and set for simplicity α ± = arcsin(k 0 ± d cosφ) (remark that K 0 ± d cosφ 1 by (4)). Suppose first of all that 0 (α φ) (φ α ) = α φ, analogously we reason if 0 (α φ) (φ α ) = φ α. Let R 0 be the robot which follows a circle with curvature K and velocity V 0. By hypothesis there exists an initial condition R 1 and controls v 1, w 1 such that robot R 1 is in (d, φ)- formation with leader R 0. If β(0) = θ 0 (0) θ 1 (0) is different from π α then set K = K 0, lim t β(t) = α cos(α and lim t v 1 (t) = V φ) 0 > V p, therefore the first inequality of (11) is false. If β(0) = θ 0 (0) θ 1 (0) = π α, take K = K 0 ǫ with ǫ ǫ) d ) φ) chosen such that V0 cos(arcsin((k 0 > V p. Since β(0) is now different from π α as before, lim t v 1 (t) > V p, which contradicts (11). If 0 (α φ) (φ α ) = 0 then take K = tan φ d (which is the solution of arcsin(kd cosφ) φ = 0); since α φ α, it follows that K0 K K 0 and reasoning as before, we get a contradiction. Therefore (6) holds. Finally to verify (9), remark that if R 0 and R 1 are in (d, φ)-formation then it is necessary that 1 d K 0 K 0 1 d (by (4)), therefore (9) follows from property c). B) A). Let R 0 be a robot which verifies trajectory constraint (10) with V 0, K0, K 0 verifying conditions (4), (5) and (6). The aim is to show that there exist initial conditions such that R 1 with controls v 1, ω 1 given by (8) is in (d, φ) formation with R 0 and constraint (11) is verified. In fact if R 1 has the controls v 1 and ω 1, by the definition of E(t), given by (3): Ė = v 0 τ(θ 0 ) (v 1 τ(θ 1 ) dν(θ 1 φ)ω 1 ) = v 0 τ(θ 0 ) cos(θ (v 0 θ 1 φ) sin(θ 0 τ(θ 1 ) dν(θ 1 φ)v 0 θ 1) 0 d ) = v 0 R(θ 0)[(, 0) T sin(θ 0 θ 1 )ν(θ 1 θ 0 φ) cos(θ 0 θ 1 φ)τ(θ 1 θ 0 )] = 0, with R(θ) = (τ(θ), ν(θ)). Choose the initial condition of the follower R 1 such that R 0 and R 1 are in (d, φ)-formation at time t = 0 and arcsin(k0 d cosφ) < θ 0(0) θ 1 (0) < arcsin(k 0 d cosφ), recall that K 0 ± d cosφ 1 by (4). By c), t 0 4

arcsin(k0 d cosφ) < θ 0(t) θ 1 (t) < arcsin(k 0 d cosφ). (17) Consider φ 0 (the case φ < 0 is analogous), then θ 0 θ 1 φ < arcsin(k 0 d cosφ) φ arcsin(1) φ π and θ 0 θ 1 φ > arcsin(k0 d cosφ) φ arcsin(cosφ) φ = π, being 1 K 0 d, K 0 d cosφ 1, therefore cos(θ v 1 = v 0 θ 1 φ) 0 > 0. Moreover from (17) and (6) it follows directly that v 1 (t) V p. Finally the curvature of the path followed by R 1 is given by κ 1 (t) = ω1(t) sin β d cos(β φ) = 1 d[cot β sin φ]. Being the function v 1(t) = (d[cot β sin φ]) 1 if β 0, β π f(β) = 0 if β = 0 monotone increasing, it follows by (5) that sign K 0 ( d [cot(arcsin(d K 1 cosφ)) sin φ] ) 1 ω1(t) v sign K ( 1(t) 0 d [cot(arcsin(d K 1 cosφ)) sinφ] ) 1 ( therefore sign K 0 ( K 0 ) d cos φ d sin φ ) 1 ω 1(t) v sign 1(t) K 0 ( ( K 0 ) d cos φ d sinφ ) 1 which implies by (7) that K p ω1(t) v 1(t) K p. Therefore all the constraints are satisfied. 4 Stabilization of the leader-follower formation Problem Set d > 0, φ : φ < π. Let R 0 = (P0 T, θ 0 ) T be a robot satisfying the trajectory constraint (V 0, K0, K 0 ) and R 1 be another robot. Find sufficient conditions on V 0, K0, K 0 that guarantee the existence of controls v 1, ω 1 such that for any initial condition R 1, R 0 and R 1 are asymptotically in (d, φ)-formation with leader R 0 (remark that v 1 and ω 1 must be such that Assumption 1 is satisfied). The proposed control strategy consists of two steps. In the first step the follower moves with maximum linear and angular velocities until its direction is sufficiently close to that of the leader in order to satisfy the condition α θ 0 θ 1 α, where α and α are related to the maximum admissible curvatures K0, K 0 of the path followed by the leader. In the second step, the follower performs the control defined in the previous section with an added stabilizing term in order to reduce the error asymptotically to zero. The stabilizing term is chosen accurately in order to satisfy constraint (11). The basic geometric idea under the stabilization is the following: the error vector E is decomposed with respect to vectors τ(θ 1 ) and ν(θ 1 φ) as shown in Fig. 3, E = E, ν(θ 1 φ) τ(θ 1 ), ν(θ 1 φ) τ(θ E, τ(θ 1 ) 1) ν(θ 1 φ), τ(θ 1 ) ν(θ 1 φ) = E, τ(θ 1 φ) τ(θ 1 ) E, ν(θ 1) ν(θ 1 φ). φ R 1 P 1 θ 1 ν(θ 1 φ) τ(θ 1) E τ E ν E τ(θ 1) P 0 R 0 Fig. 3. Error decomposition, where E τ = E, τ(θ 1φ) E ν = E, ν(θ 1). and The stabilizing controller adds correcting terms proportional to the error components to equations (8). To ensure that the physical constraint of the follower is satisfied, the correcting terms are multiplied by a time-varying gain η(t) that must be chosen in a suitable way (see equation (9)). In the following theorem S 1 denotes the quotient space R/R equipped with the canonical topology being R the equivalence relation, x y x y = nπ, n Z, where Z is the integer set. Theorem Set d > 0, φ : φ < π and R 0, R 1 R 3. Let R 0 = (P0 T, θ 0) be a robot with initial condition R 0, satisfying the trajectory constraint (V 0, K0, K 0 ). Suppose that the following properties hold: 0 < W 0 v 0 (t) (18) 1 d < K 0 K 0 < 1 d, if φ 0 1 d < K 0 K 0 < 1 d, if φ < 0 (19) K 0 < K 0 K 0 < K 0 (0) V 0 cos ( 0 (arcsin(k 0 d cosφ) φ) (φ arcsin(k0 d cosφ))) < V p cosφ (1) where K ± 0 = (sign K± p ) ( ((K ± p ) 1 d sin φ) d cos φ ) 1. () Then there exists ǫ > 0 such that for any ǫ : 0 < ǫ < ǫ, for any robot R 1 = (P T 1, θ 1 ) T with initial condition R 1, there exist suitable controls v 1, ω 1 such that R 0 and R 1 are asymptotically in (d, φ)-formation and t 0 : t t arcsin((k 0 ǫ)dcosφ) θ 0(t) θ 1 (t) arcsin((k 0 ǫ)dcosφ). (3) PROOF. Take ǫ > 0 such that 1 d < K 0 ǫ K 0 ǫ < 1 d, if φ 0 1 d < K 0 ǫ K 0 ǫ < 1 d, if φ < 0 (4) 5

K 0 < K 0 ǫ K 0 ǫ < K 0 (5) V 0 cos ( 0 (arcsin((k 0 ǫ)dcosφ) φ) (φ arcsin((k0 ǫ)dcosφ))) < V p cosφ (6) and take any ǫ : 0 < ǫ ǫ. Define Γ ǫ = {x S 1 (K0 ǫ)dcosφ sin x (K 0 ǫ)dcosφ}. Set the controls as V p, if θ 0 (t) θ 1 (t) / Γ ǫ v 1 (t) = v 0(t)cos(θ 0(t) θ 1(t) φ)η(t) E(t), τ(θ 1(t)φ), if θ 0 (t) θ 1 (t) Γ ǫ (7) V p K p, if θ 0(t) θ 1 (t) / Γ ǫ and K p 0 V p Kp ω 1 (t) =, if θ 0(t) θ 1 (t) / Γ ǫ and K p < 0 v 0(t)sin(θ 0(t) θ 1(t))η(t) E(t), ν(θ 1(t)) d, where η(t) is a function given by η(t) = if θ 0 (t) θ 1 (t) Γ ǫ (8) (v0 W0/) cos(θ0 θ1 φ) E, τ(θ 1 φ) [(K 0 ǫ/ κ0) (κ0 (K 0 ǫ/))] d E, ν(θ 1) Vp v0 cos(θ0 θ1 φ) E, τ(θ 1 φ) v 0 K p d cos(θ 0 θ 1 φ) sin(θ 0 θ 1) E, ν(θ 1) K p E, τ(θ 1 φ) v 0 sin(θ 0 θ 1) K p d cos(θ 0 θ 1 φ) E, ν(θ 1) K p E, τ(θ 1 φ) M (9) and M is a positive gain constant (with the convention that 1 0 = ). Set β(t) = θ 0(t) θ 1 (t), t 0. First of all we remark that t 0 : β( t) Γ ǫ. In fact, suppose for instance that K p 0, then if t 0, β(t) / Γ ǫ, by (5): β(t) = ω0 (t) ω 1 (t) = κ 0 (t)v 0 (t) K p V p K 0 v 0(t) K p V p ( K 0 v 0(t) K p V p) ǫv 0 (t) ( K 0 V 0 K p V p) ǫw 0 ǫw 0, being ( K 0 V 0 K p V p) 0. In fact, suppose for simplicity that cos(0 (arcsin((k 0 ǫ)d cosφ) φ) (φ arcsin((k0 ǫ)d cosφ))) = cos(0) = 1, by (11) and (6) K 0 V 0 K p V p { ((K p ) 1 d sin φ) d cos φ } 1/ Vp cosφ K p V p V p { ((K p ) 1 d sin φ) d cos φ } 1/ (cosφ { cos φ (K p d sinφ) } 1/ ) 0. Therefore β(t) ǫw0 t β(t 0 ), t 0, which implies straightaway property (3). Set β 1 (Γ ǫ ) = {t 0 β(t) Γ ǫ }, then by (8), t β 1 (Γ ǫ ): β(t) = ω0 (t) ω 1 (t) = ω 0 (t) v 0(t)sin β(t)η(t) E(t), ν(θ 1(t)) d = v0(t) η(t) E(t), ν(θ1(t)) sinβ(t)) d d (κ 0(t)d, which implies by definition (9) of η(t) that if β( t) = arcsin((k 0 ǫ)d cosφ), (β( t) = arcsin((k0 ǫ)dcosφ)) then β( t) ǫv0, ( β( t) ǫw0 ). This implies that t [0, t) t 0 such that t t, β(t) Γ ǫ and β(t) / Γ ǫ (30) which implies (3). To prove that the physical constraint (11) is verified for v 1, remark that by (7) and (30), v 1 (t) = V p, t [0, t) and t t v0(t)cos(β(t) φ) η(t) E(t), τ(θ1(t) φ) v 1(t) =. (31) Therefore by definition of η(t) and (18), v 1 (t) v 0(t)cos(β(t) φ) η(t) E(t), τ(θ 1(t)φ) W0 cos(β(t) φ). Therefore v 1 (t) > 0, t 0, by the following property: c 1 > 0 : cos(β(t) φ) c 1, t t. (3) In fact suppose for instance that φ > 0, by (3) and (4) β(t) φ arcsin((k 0 ǫ)dcosφ) φ < arcsin(1) φ = π φ and β(t) φ arcsin((k 0 ǫ)dcosφ) φ > arcsin() φ = π which implies (3). Furthermore by (31) and (9), v 1 (t) V p, t 0. To verify constraint (11) for κ 1 (t), remark first of all that it is verified by (7), (8) if t [0, t). If t t : κ 1 (t) = v 0(t)sin β(t)η(t) E(t), ν(θ 1(t)) κ 1 (t) ω 1(t) v 1(t) = dv 0(t)cos(β(t) φ)η(t) E(t), τ(θ 1(t)φ) v 0(t)sin β(t)η(t) E(t), ν(θ 1(t)) dv 0(t)cos(β(t) φ) η(t) sign K p E(t), τ(θ 1(t)φ) v 0(t)(K p d cos(β(t) φ) sin β(t)) K p, since, by (9), η(t) E(t), ν(θ 1(t)) K p E(t), τ(θ 1(t)φ) and analogously, κ 1 (t) Kp, t t ; therefore constraint (11) is completely verified. To conclude the proof it remains to verify that R 0 andr 1 are asymptotically in (d, φ)-formation. Differentiating the error E(t), by (7) and (8), as in the proof of Theorem 1, we get that t t : Ė = v 0 (t)τ(θ 0 (t)) v 0 (t) ( cos(β(t) φ) τ(θ 1 (t)) d sin β(t) ν(θ 1(t) φ) ) η(t) ( E(t), τ(θ 1(t)φ) τ(θ 1 (t)) E(t), ν(θ1) ν(θ 1 (t)φ) ) = η E(t), since w, w 1, w R such that w 1, w 0, w = w, w w 1, w w 1 w, w 1 w, w1 w. Therefore d dt ( E(t) ) = η(t)( E(t) ), t t and then lim t E(t) = 0 since the following property holds, ( ) c c > 0 such that η(t) E(t) M. (33) In fact to verify (33), first of all remark that by (18) it follows straightaway that ( K 0 ǫ κ 0(t) ) ( κ 0 (t) (K0 ǫ )) ǫ, t 0. Moreover by (6), V p cosφ v 0 (t)cos(θ 0 (t) θ 1 (t) φ) V p cosφ V 0 cos(0 (arcsin(k 0 d cosφ) φ) (φ arcsin(k 0 d cosφ))) = 6

6 4 1 0.8 0.6 E E 1 [m] y Leader Follower 0.4 0. 0 0 0 4 6 8 10 1 14 time [s] 0 4 x [m] Fig. 4. Trajectory of the robots. c > 0 and furthermore by (3), t t, K p sin β(t) d cos(β(t) φ) K p sign (K 0 ǫ) (K 0 ǫ) d cos φd sin φ > 0, since (K 0 ǫ) < K 0, which implies that c 3 > 0 such that K p d cos(β(t) φ) sin β(t) c 3 ; analogously c 3 > 0 such that sinβ(t) K p d cos(β(t) φ) c 3. Therefore bringing together (3) with the previous inequalities, we obtain (33) by the definition of η. 5 Simulation results Fig. 4 and 5 show the results of the simulation experiment we conducted to test the effectiveness of the stabilizing controller presented in Sect. 4. The leader R 0 moves along a circular path with v 0 (t) = 1.5 m/s, ω 0 (t) = 0.4 rad/s. The initial conditions are R 0 = (5,, π/), R 1 = (3, 1.5, π/8) and d = 1 m, φ = π/3 rad. Moreover, W 0 = 1 m/s, V 0 = m/s, K0 = 1 rad/m, K 0 = 0.5 rad/m, V p = 4 m/s, Kp = rad/m, K p = 3 rad/m, ǫ = 0.05 rad/m and M = 1 rad/m. Fig. 4 depicts the trajectory of the leader R 0 (solid) and the follower R 1 (dash) and the arcs of circle A d (θ 0 (t) φ π, arcsin((k 0 ǫ)d cosφ), arcsin((k 0 ǫ)d cosφ)) introduced in Remark 1(the position of the robots is reported in Fig. 4 each second). R 0 and R 1 are in (1, π/3)-formation approximately at time t = 6 s. At steady state R 1 keeps on the arcs of circle. Since the bounds and parameters chosen in the simulation experiment satisfy equations (18), (4), (5) and (6), by applying controls (7),(8) from Theorem lim t E(t) = 0 (see Fig. 5), and conditions (11), (3) hold. References Fig. 5. Error vector E(t) = (E 1, E ) T. Balch, T. and R.C. Arkin (1998). Behavior-based formation control for multirobot teams. IEEE Trans. Robot. Automat. 14(6), 96 939. Consolini, L., F. Morbidi, D. Prattichizzo and M. Tosques (006). On the Control of a Leader-Follower Formation of Nonholonomic Mobile Robots. In: Proc. IEEE Int. Conf. Decision and Control. pp. 599 5997. Das, A.K., R. Fierro, V. Kumar, J.P. Ostrowsky, J. Spletzer and C. Taylor (00). A Vision-Based Formation Control Framework. IEEE Trans. Robot. Automat. 18(5), 813 85. Do, K.D. and J. Pan (007). Nonlinear formation control of unicycle-type mobile robots. Robotics and Autonomous Systems 55, 191 04. Edwards, D.B., T.A. Bean, D.L. Odell and M.J. Anderson (004). A leader-follower algorithm for multiple AUV formations. In: Proc. IEEE/OES Autonomous Underwater Vehicles. pp. 40 46. Fax, J.A. and R.M. Murray (004). Information Flow and Cooperative Control of Vehicle Formations. IEEE Trans. Automat. Contr. 49(9), 1465 1476. Fierro, R., C. Belta, J.P. Desai and V. Kumar (001). On controlling aircraft formations. In: Proc. IEEE Int. Conf. Decision and Control. Vol.. pp. 1065 1070. Ghabcheloo, R., A. Pascoal, Silvestre and I. Kaminer (006). Coordinated path following control of multiple wheeled robots using linearization techniques. Int. J. Systems Science 37(6), 399 414. Giulietti, F., L. Pollini and M. Innocenti (000). Autonomous formation flight. IEEE Contr. Syst. Mag. 0(6), 34 44. Koo, T.J. and S.M. Shahruz (001). Formation of a group of unmanned aerial vehicles (UAVs). In: Proc. American Control Conf.. Vol. 1. pp. 69 74. Lawton, J.R., R.W. Beard and B.J. Young (003). A Decentralized Approach to Formation Maneuvers. IEEE Trans. Robot. Automat. 19(6), 933 941. Lewis, M.A. and K.H. Tan (1997). High Precision Formation Control of Mobile Robots Using Virtual Structures. Autonomous Robots 4(4), 387 403. Lin, Z., B.A. Francis and M. Maggiore (005). Necessary and Sufficient Graphical Conditions for Formation Control of Unicycles. IEEE Trans. Automat. Contr. 50(1), 11 17. Mariottini, G.L., F. Morbidi, D. Prattichizzo, G.J. Pappas and K. Daniilidis (007). Leader-Follower Formations: Uncalibrated Vision-Based Localization and Control. Proc. IEEE Int. Conf. Robot. Automat. pp. 403 408. 7

Marshall, J.A., M.E. Broucke and B.A. Francis (004). Formations of Vehicles in Cyclic Pursuit. IEEE Trans. Automat. Contr. 49(11), 1963 1974. Singh, S.N., P. Chandler, C. Schumacher, S. Banda and M. Pachter (000). Adaptive feedback linearizing nonlinear close formation control of UAVs. In: Proc. American Control Conf.. Vol.. pp. 854 858. Skjetne, R., S. Moi and T.I. Fossen (00). Nonlinear formation control of marine craft. In: Proc. IEEE Int. Conf. Decision and Control. Vol.. pp. 1699 1704. 8