Closed loop steering of unicycle like vehicles via Lyapunov techniques

Aicardi, M.; Casalino, Giuseppe; Bicchi, Antonio; Balestrino, Alessandro

doi:10.1109/100.388294

Cited by 416 publications

(244 citation statements)

References 4 publications

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“…So we have three constraint equations of the vehicle motioṅ0 siṅ0 cos = 0, 0 coṡ0 siṅ=̇, 0 coṡ0 siṅ=̇ ( 9) e constraints above can be written in the Pfaffian form (2). From (3), the Jacobian matrix is…”

Section: Dynamic and Kinematic Model Of A Constrained Nonholonomic Vementioning

confidence: 99%

“…In fact there are three generalized coordinates that is, lateral position, longitudinal position, and vehicle orientation to be controlled, while there are two control inputs only, that is, steering and longitudinal inputs. Several approaches have been proposed for the synthesis of kinematical controllers for vehicles with nonholonomic constraints on the motion [2][3][4]. e kinematical controller is essential to guarantee the vehicle motion along the direction of the orientation.…”

Section: Introductionmentioning

confidence: 99%

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A Theoretical and Experimental Approach of Fuzzy Adaptive Motion Control for Wheeled Autonomous Nonholonomic Vehicles

Melluso

2013

ISRN Robotics

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A new fuzzy adaptive control is applied to solve a problem of motion control of nonholonomic vehicles with two independent wheels actuated by a differential drive. e major objective of this work is to obtain a motion control system by using a new fuzzy inference mechanism where the Lyapunov stability can be ensured. In particular the parameters of the kinematical control law are obtained using a fuzzy mechanism, where the properties of the fuzzy maps have been established to have the stability above. Due to the nonlinear map of the intelligent fuzzy inference mechanism (i.e., fuzzy rules and value of the rule), the parameters above are not constant, but, time aer time, based on empirical fuzzy rules, they are updated in function of the values of the tracking errors. Since the fuzzy maps are adjusted based on the control performances, the parameters updating ensures a robustness and fast convergence of the tracking errors. Also, since the vehicle dynamics and kinematics can be completely unknown, dynamical and kinematical adaptive controllers have been added. e proposed fuzzy controller has been implemented for a real nonholonomic electrical vehicle. erefore, system robustness and stability performance are veri�ed through simulations and experimental studies.

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Section: Dynamic and Kinematic Model Of A Constrained Nonholonomic Vementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Theoretical and Experimental Approach of Fuzzy Adaptive Motion Control for Wheeled Autonomous Nonholonomic Vehicles

Melluso

2013

ISRN Robotics

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“…As for posture stabilization, both discontinuous and/or time-varying feedback controllers have been proposed. Smooth time-varying stabilization was pioneered by Samson [27,28], while discontinuous (often, time-varying) control was used in various forms, e.g., see [2,9,21,22,32]. A recent addition to this class was presented in [14], where dynamic feedback linearization has been extended to the posture stabilization problem.…”

Section: Introductionmentioning

confidence: 99%

“…This approach has been proposed in [2], where a Lyapunov-like design of a posture stabilizing controller is carried out using a polar coordinate transformation. The control law, once rewritten in terms of the original state variables, is discontinuous at the origin of the configuration space Q.…”

Section: Control Based On Polar Coordinatesmentioning

confidence: 99%

Control of Wheeled Mobile Robots: An Experimental Overview

Luca

Oriolo

Vendittelli

2001

Ramsete

125

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The subject of this chapter is the motion control problem of wheeled mobile robots (WMRs). With reference to the unicycle kinematics, we review and compare several control strategies for trajectory tracking and posture stabilization in an environment free of obstacles. Experiments are reported for SuperMARIO, a two-wheel differentially-driven mobile robot. From the comparison of the obtained results, guidelines are provided for WMR end-users.

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“…For wheeled mobile robots, conventional control laws have been applied for solving tracking problems [58,30,32,43,1,23,49] and stabilization problems [3,17,51,54,8]. For example, see [29,28,39,48,12,14] for backstepping methods [11,24,53] for sliding mode control, [9,34,18] for moving horizon H ∞ tracking control coupled with disturbance effect, and [47] for transverse function approach.…”

Section: Introductionmentioning

confidence: 99%

RFID-Based Mobile Robot Trajectory Tracking and Point Stabilization Through On-line Neighboring Optimal Control

Miah

Gueaieb

2014

J Intell Robot Syst

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In this manuscript, we propose an on-line trajectorytracking algorithm for nonholonomic Differential-Drive Mobile Robots (DDMRs) in the presence of possibly large parametric and measurement uncertainties. Most mobile robot tracking techniques that depend on reference RF beacons rely on approximating line-of-sight (LOS) distances between these beacons and the robot. The approximation of LOS is mostly performed using Received Signal Strength (RSS) measurements of signals propagating between the robot and RF beacons. However, accurate mapping between RSS measurements and LOS distance remains a significant challenge and is almost impossible to achieve in an indoor reverberant environment. This paper contributes to the development of a neighboring optimal control strategy where the two major control tasks, trajectory tracking and point stabilization, are solved and treated as a unified manner using RSS measurements emitted from Radio Frequency IDentification (RFID) tags. The proposed control scheme is divided into two cascaded phases. The first phase provides the robot's nominal control inputs (speeds) and its trajectory using full-state feedback. In the second phase, we design the neighboring optimal controller, where RSS measurements are used to better estimate the robot's pose by employing an optimal filter. Simulation and experimental results are presented to demonstrate the performance of the proposed optimal feedback controller for solving the stabilization and trajectory tracking problems using a DDMR. Keywords Mobile robot navigation · RFID systems · optimal control · trajectory tracking · robot stabilization · nonholonomic systems. Frequently Used Symbols K(t)Feedback control gain at time t H K Hamiltonian's gradient with respect to K s Number of RFID tags in the environment ψ Costate variable (Lagrange multiplier)Robot's actual and desired pose at time t q j t ∈ R 3 jth tag position in 3D space t 0 ,t f Initial and final time instantsRobot's control input vector at time t ξ (t) Robot's actuator noise at time t ζ (t)Measurement noise vector at time t (·) o , (·) ε , (·) ad Optimal, perturb, admissible value of (·) L Lebesgue measurable function space ν T dJ(·) Gateaux (directional) derivative of J in direction ν 1 Introduction

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Closed loop steering of unicycle like vehicles via Lyapunov techniques

Cited by 416 publications

References 4 publications

A Theoretical and Experimental Approach of Fuzzy Adaptive Motion Control for Wheeled Autonomous Nonholonomic Vehicles

A Theoretical and Experimental Approach of Fuzzy Adaptive Motion Control for Wheeled Autonomous Nonholonomic Vehicles

Control of Wheeled Mobile Robots: An Experimental Overview

RFID-Based Mobile Robot Trajectory Tracking and Point Stabilization Through On-line Neighboring Optimal Control

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