Simultaneous distributed localization, mapping and formation control of mobile robots based on local relative measurements

Guo, Miao; Jayawardhana, Bayu; Lee, Jin Gyu; Shim, Hyungbo

doi:10.1016/j.ifacol.2020.12.2454

Cited by 5 publications

(6 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approximation enables us to design a simple nonlinear observer. As will be shown later in the numerical simulation, the proposed observer based on this approximation works robustly when the actual bearing dynamics is simulated based on (2).…”

Section: A Systems Description and Problem Formulationmentioning

confidence: 86%

“…This is in line with Assumption 1 where a sufficiently small T u(k) is required. Since the denominators in (13) depend on l * − p(k) 2 the estimator gain becomes larger the closer the mobile agent gets to the landmark. However, this is compensated by the requirement that T u(k) must be small in order to ensure the validity of small-angle approximation.…”

Section: A Contraction Analysismentioning

confidence: 99%

See 1 more Smart Citation

Range-Only Bearing Estimator for Localization and Mapping

Marcantoni

Jayawardhana

Bunte

2023

IEEE Control Syst. Lett.

Self Cite

View full text Add to dashboard Cite

Navigation and exploration within unknown environments are typical examples in which simultaneous localization and mapping (SLAM) algorithms are applied. When mobile agents deploy only range sensors without bearing information, the agents must estimate the bearing using the online distance measurement for the localization and mapping purposes. In this letter, we propose a scalable dynamic bearing estimator to obtain the relative bearing of the static landmarks in the local coordinate frame of a moving agent in real-time. Using contraction theory, we provide convergence analysis of the proposed range-only bearing estimator and present upper and lower-bound for the estimator gain. Numerical simulations demonstrate the effectiveness of the proposed method.

show abstract

Section: A Systems Description and Problem Formulationmentioning

confidence: 86%

Section: A Contraction Analysismentioning

confidence: 99%

Range-Only Bearing Estimator for Localization and Mapping

Marcantoni

Jayawardhana

Bunte

2023

IEEE Control Syst. Lett.

Self Cite

View full text Add to dashboard Cite

show abstract

“…We assume that the moving landmarks (which can also include the static landmarks as considered in Guo etal. 15 ) follow periodic trajectories that can be generated by an exosystem, such as, those used in surveillance tasks or repetitive tasks by autonomous robots. Secondly, we put forward distributed formation control and centroid tracking control based on the combined information from the estimated map and from the local measurement.…”

Section: Introductionmentioning

confidence: 99%

“…Thirdly, we analyze the robustness of the proposed observer and control design with respect to the external 2 disturbance signals. In comparison to our previous work 15 , we have relaxed the assumptions in Guo etal. 15 , where all landmarks are assumed to be static and each agent observes the origin of the global frame consistently.…”

Section: Introductionmentioning

confidence: 99%

Maintaining and steering a formation in an unknown dynamic environment via a consistent distributed dynamic map

Guo,

Jayawardhana,

Lee

et al. 2024

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

In this paper, we study the problem of maintaining a stable mobile robot formation, steering and localizing all robots in an unknown dynamic environment consisting of multiple periodically moving objects, without the presence of a global positioning system or a robot tracking system. We propose a distributed observer such that each agent can estimate global positions of all mobile robots and that of moving landmarks in an unknown environment. By combining the proposed distributed observer with the distributed formation control and centroid tracking control law, we show that the formation shape can be maintained by utilizing its available relative measurements and the estimated relative measurements to its neighbors, and the group's centroid follows a desired trajectory. We present stability analysis of the closed‐loop system. Finally, we validate the proposed methods in a simulation result where a group of mobile robots can maintain a robust formation and maneuver in an unknown dynamic environment.

show abstract

“…Examples include the use of distributed optimization to solve economic dispatch problems, i.e. to minimize the total generation cost under the power supply-demand balance and individual generation capacity constraints [7], distributed state estimation for the design of sensor networks where each sensor node can autonomously collect, manage, and control the information [8,9], and the distributed SLAM problem where the goal is to make a group of mobile robots simultaneously localize and map the environment [10].…”

Section: Introductionmentioning

confidence: 99%

Node-wise monotone barrier coupling law for central pattern generation

Lee¹,

Mostajeran²,

Goffrier³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

With the aim of providing new insights into the mechanisms behind the emergence of collective behaviors via nonlinear coupling, we propose a node-wise monotone barrier coupling law that imitates the behavior and beneficial properties of neural central pattern generators (CPGs). In particular, the coupling law 1) allows us to assign multiple central patterns on the circle and 2) allows for rapid switching between different patterns via simple 'kicks'. In the end, we achieve full control by partitioning the state space by utilizing a barrier effect and assigning unique steady-state behaviors to each element of the resulting partition. We analyze the global behavior and study the viability of the design.

show abstract

Simultaneous distributed localization, mapping and formation control of mobile robots based on local relative measurements

Cited by 5 publications

References 10 publications

Range-Only Bearing Estimator for Localization and Mapping

Range-Only Bearing Estimator for Localization and Mapping

Maintaining and steering a formation in an unknown dynamic environment via a consistent distributed dynamic map

Node-wise monotone barrier coupling law for central pattern generation

Contact Info

Product

Resources

About