Ant-Based Multi-Robot Exploration in Non-Convex Space without Global-Connectivity Constraints

Cardona, Gustavo A.; Yanguas-Rojas, David; Arévalo-Castiblanco, Miguel F.; Mojica‐Nava, Eduardo

doi:10.23919/ecc.2019.8796034

Cited by 13 publications

(10 citation statements)

References 13 publications

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“…Heterogeneous multi-robot exploration, foraging, and coverage have been widely studied in robotics literature [4]- [6]. Recent works consider communication restricted or intermittent connectivity by modeling ways to maintain connectivity while exploring [1], to account for momentary disconnection [7], or dropping intermediary notifications to other robots [8]. Authors in [9] use a decentralized Markov decision process to estimate future locations of robots when interrobot messages are delayed at a stochastic rate.…”

Section: Related Workmentioning

confidence: 99%

Coordinated Multi-Agent Exploration, Rendezvous, & Task Allocation in Unknown Environments with Limited Connectivity

Bramblett

Peddi

Bezzo

2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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In communication restricted environments, a multi-robot system can be deployed to either: i) maintain constant communication but potentially sacrifice operational efficiency due to proximity constraints or ii) allow disconnections to increase environmental coverage efficiency, challenges on how, when, and where to reconnect (rendezvous problem). In this work we tackle the latter problem and notice that most stateof-the-art methods assume that robots will be able to execute a predetermined plan; however system failures and changes in environmental conditions can cause the robots to deviate from the plan with cascading effects across the multi-robot system. This paper proposes a coordinated epistemic prediction and planning framework to achieve consensus without communicating for exploration and coverage, task discovery and completion, and rendezvous applications. Dynamic epistemic logic is the principal component implemented to allow robots to propagate belief states and empathize with other agents. Propagation of belief states and subsequent coverage of the environment is achieved via a frontier-based method within an artificial physics-based framework. The proposed framework is validated with both simulations and experiments with unmanned ground vehicles in various cluttered environments.

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Section: Related Workmentioning

confidence: 99%

Coordinated Multi-Agent Exploration, Rendezvous, & Task Allocation in Unknown Environments with Limited Connectivity

Bramblett

Peddi

Bezzo

2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…Corollary 1. Consider a network of N heterogeneous agents with unknown parameters and a reference model (12), then, the synchronization of this network is achieved from the control protocol (36) and the adaptive laws (39).…”

Section: Proof It Follows Proposition 1 Of Reference 20 ▪mentioning

confidence: 99%

“…11 Nowadays, the focus of researchers is to strengthen these applications with robust algorithms and complex scenarios. 12 Along with scientific advancement, the inclusion of robust and indirect adaptive control laws has been used to solve control problems that present uncertainties in their dynamics in a distributed environment. 13,14 Some of the latest results…”

Section: Introductionmentioning

confidence: 99%

Indirect adaptive synchronization for a heterogeneous multiagent network

Arévalo-Castiblanco

Tellez‐Castro

Mojica‐Nava

2022

Adaptive Control & Signal

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This article studies the problem of indirect adaptive state feedback control for a heterogeneous MIMO network with input and matched uncertainties. A mechanical network composed of two-wheeled robots is proposed to validate the developed methodology. Within the network, a reference system is defined, and each robot has wireless communication between them. Likewise, for control design, specific adaptive laws are adopted through matching conditions to approximate the dynamics of each agent, which are partially unknown and constructed. The inclusion of an optimal adaptive modification is considered for the suppression of input uncertainties. This methodology, along with the distributed adaptive control and identification, is validated with Lyapunov-based stability analysis. The presented control scheme guarantees that all closed-loop signals are bounded and ensures that synchronization errors converge asymptotically to zero. Finally, simulations oriented to the application problem mentioned are presented to validate the effectiveness of the control scheme.

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“…In the same way, in [2] it is explained why it is vital to act on the affected Ì ISSN: 2088-8708 area within 48 hours of the incident due to the probability of finding survivors gets significantly reduced after that period. Bearing in mind that time is crucial, applying robotics to SAR missions seems to be advantageous, relying on the robots' ability to carry out tasks efficiently in conditions that might be adverse for human rescuers as presented in [3]. Likewise, there are works as [4,5] that show the possibility of employing robot swarms capable of behave cooperatively with humans improving the tasks performance.…”

Section: Introductionmentioning

confidence: 99%

Visual victim detection and quadrotor-swarm coordination control in search and rescue environment

Cardona

Ramirez-Rugeles

Mojica‐Nava

et al. 2021

IJECE

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We propose a distributed victim-detection algorithm through visual information on quadrotors using convolutional neuronal networks (CNN) in a search and rescue environment. Describing the navigation algorithm, which allows quadrotors to avoid collisions. Secondly, when one quadrotor detects a possible victim, it causes its closest neighbors to disconnect from the main swarm and form a new sub-swarm around the victim, which validates the victim’s status. Thus, a formation control that permits to acquire information is performed based on the well-known rendezvous consensus algorithm. Finally, images are processed using CNN identifying potential victims in the area. Given the uncertainty of the victim detection measurement among quadrotors’ cameras in the image processing, estimation consensus (EC) and max-estimation consensus (M-EC) algorithms are proposed focusing on agreeing over the victim detection estimation. We illustrate that M-EC delivers better results than EC in scenarios with poor visibility and uncertainty produced by fire and smoke. The algorithm proves that distributed fashion can obtain a more accurate result in decision-making on whether or not there is a victim, showing robustness under uncertainties and wrong measurements in comparison when a single quadrotor performs the mission. The well-functioning of the algorithm is evaluated by carrying out a simulation using V-Rep.

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Ant-Based Multi-Robot Exploration in Non-Convex Space without Global-Connectivity Constraints

Cited by 13 publications

References 13 publications

Coordinated Multi-Agent Exploration, Rendezvous, & Task Allocation in Unknown Environments with Limited Connectivity

Coordinated Multi-Agent Exploration, Rendezvous, & Task Allocation in Unknown Environments with Limited Connectivity

Indirect adaptive synchronization for a heterogeneous multiagent network

Visual victim detection and quadrotor-swarm coordination control in search and rescue environment

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