HDec-POSMDPs MRS Exploration and Fire Searching Based on IoT Cloud Robotics

Shenawy, Ayman El; Mohamed, Khalil; Harb, Hany M.

doi:10.1007/s11633-019-1187-6

Cited by 12 publications

(7 citation statements)

References 59 publications

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“…The majority of distributed coverage algorithms depend on either a globally connected network or a limited, asynchronous communication within a small, finite amount of time ( El Shenawy et al., 2020 ; Hu et al., 2020 ). Many overcome this limitation by simply choosing the closest Frontier point to a robot ( Cesare et al., 2015 ) or retaining the last position of the robot and only sharing information if the robots wander within range ( Colares and Chaimowicz, 2016 ).…”

Section: Approachmentioning

confidence: 99%

Epistemic planning for multi-robot systems in communication-restricted environments

Bramblett

Bezzo

2023

Front. Robot. AI

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Many real-world robotic applications such as search and rescue, disaster relief, and inspection operations are often set in unstructured environments with a restricted or unreliable communication infrastructure. In such environments, a multi-robot system must either be deployed to i) remain constantly connected, hence sacrificing operational efficiency or ii) allow disconnections considering when and how to regroup. In communication-restricted environments, we insist that the latter approach is desired to achieve a robust and predictable method for cooperative planning. One of the main challenges in achieving this goal is that optimal planning in partially unknown environments without communication requires an intractable sequence of possibilities. To solve this problem, we propose a novel epistemic planning approach for propagating beliefs about the system’s states during communication loss to ensure cooperative operations. Typically used for discrete multi-player games or natural language processing, epistemic planning is a powerful representation of reasoning through events, actions, and belief revisions, given new information. Most robot applications use traditional planning to interact with their immediate environment and only consider knowledge of their own state. By including an epistemic notion in planning, a robot may enact depth-of-reasoning about the system’s state, analyzing its beliefs about each robot in the system. In this method, a set of possible beliefs about other robots in the system are propagated using a Frontier-based planner to accomplish the coverage objective. As disconnections occur, each robot tracks beliefs about the system state and reasons about multiple objectives: i) coverage of the environment, ii) dissemination of new observations, and iii) possible information sharing from other robots. A task allocation optimization algorithm with gossip protocol is used in conjunction with the epistemic planning mechanism to locally optimize all three objectives, considering that in a partially unknown environment, the belief propagation may not be safe or possible to follow and that another robot may be attempting an information relay using the belief state. Results indicate that our framework performs better than the standard solution for communication restrictions and even shows similar performance to simulations with no communication limitations. Extensive experiments provide evidence of the framework’s performance in real-world scenarios.

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Section: Approachmentioning

confidence: 99%

Epistemic planning for multi-robot systems in communication-restricted environments

Bramblett

Bezzo

2023

Front. Robot. AI

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“…Several works have also included system failures or disturbances in multirobot exploration policies, such as in the work [10]; however, the policy assumes robots are able to communicate these disruptions. In most approaches, the execution policy is static and communication is a constraint that either needs to be satisfied for all time or at a defined location [11], [12].…”

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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“…The actuality and originality of this research are articulated by addressing how IoRT systems leverage environment monitoring mechanisms [105][106][107][108] to aggregate sensor data and map networked processes [109][110][111][112] by use of decision and control algorithms. Robotic coordination mechanisms and cooperative actions [113][114][115][116] optimize object perception and tracking [117][118][119][120] in dynamic unknown environments. Our particular contribution is to clarify how data mining, fusion, and processing [121][122][123][124] assists sensor equipment through machine and deep learning algorithms.…”

Section: Introductionmentioning

confidence: 99%

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

et al. 2022

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The purpose of our systematic review was to inspect the recently published research on Internet of Robotic Things (IoRT) and harmonize the assimilations it articulates on remote big data management tools, sensing and computing technologies, and visual perception and environment mapping algorithms. The research problems were whether robotic manufacturing processes and industrial wireless sensor networks shape IoRT and lead to improved product quality by use of remote big data management tools, whether IoRT devices communicate autonomously regarding event modeling and forecasting by leveraging machine learning and clustering algorithms, sensing and computing technologies, and image processing tools, and whether smart connected objects, situational awareness algorithms, and edge computing technologies configure IoRT systems and cloud robotics in relation to distributed task coordination through visual perception and environment mapping algorithms. A Shiny app was harnessed for Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to configure the flow diagram integrating evidence-based gathered and processed data (the search outcomes and screening procedures). A quantitative literature review of ProQuest, Scopus, and the Web of Science databases was carried out throughout June and October 2022, with search terms including “Internet of Robotic Things” + “remote big data management tools”, “sensing and computing technologies”, and “visual perception and environment mapping algorithms”. Artificial intelligence and intelligent workflows by use of AMSTAR (Assessing the Methodological Quality of Systematic Reviews), Dedoose, DistillerSR, and SRDR (Systematic Review Data Repository) have been deployed as data extraction tools for literature collection, screening, and evaluation, for document flow monitoring, for inspecting qualitative and mixed methods research, and for establishing robust outcomes and correlations. For bibliometric mapping by use of data visualization, Dimensions AI was leveraged and with regards to layout algorithms, VOSviewer was harnessed.

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HDec-POSMDPs MRS Exploration and Fire Searching Based on IoT Cloud Robotics

Cited by 12 publications

References 59 publications

Epistemic planning for multi-robot systems in communication-restricted environments

Epistemic planning for multi-robot systems in communication-restricted environments

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

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

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