1,990 research outputs found
Adoption of vehicular ad hoc networking protocols by networked robots
This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan
Maintaining network connectivity and performance in robot teams
In this paper, we present an experimental study of strategies for maintaining end-to-end communication links for tasks such as surveillance, reconnaissance, and target search and identification, where team connectivity is required for situational awareness. Our main contributions are three fold: (a) We present the construction of a radio signal strength map that can be used to plan multi-robot tasks and also serve as useful perceptual information. We show how a nominal model of an urban environment obtained by aerial surveillance is used to generate strategies for exploration. (b) We present reactive controllers for communication link maintenance; and (c) we consider the differences between monitoring signal strength versus data throughput. Experimental results, obtained using our multi-robot testbed in three representative urban environments, are presented with each of our main contributions
ACHORD: communication-aware multi-robot coordination with intermittent connectivity
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksCommunication is an important capability for multi-robot exploration because (1) inter-robot communication (comms) improves coverage efficiency and (2) robot-to-base comms improves situational awareness. Exploring comms-restricted (e.g., subterranean) environments requires a multi-robot system to tolerate and anticipate intermittent connectivity, and to carefully consider comms requirements, otherwise mission-critical data may be lost. In this paper, we describe and analyze ACHORD (Autonomous & Collaborative High-Bandwidth Operations with Radio Droppables), a multi-layer networking solution which tightly co-designs the network architecture and high-level decision-making for improved comms. ACHORD provides bandwidth prioritization and timely and reliable data transfer despite intermittent connectivity. Furthermore, it exposes low-layer networking metrics to the application layer to enable robots to autonomously monitor, map, and extend the network via droppable radios, as well as restore connectivity to improve collaborative exploration. We evaluate our solution with respect to the comms performance in several challenging underground environments including the DARPA SubT Finals competition environment. Our findings support the use of data stratification and flow control to improve bandwidth-usage.Peer ReviewedPostprint (author's final draft
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
Communication for Teams of Networked Robots
There are a large class of problems, from search and rescue to environmental monitoring, that can benefit from teams of mobile robots in environments where there is no existing infrastructure for inter-agent communication. We seek to address the problems necessary for a team of small, low-power, low-cost robots to deploy in such a way that they can dynamically provide their own multi-hop communication network. To do so, we formulate a situational awareness problem statement that specifies both the physical task and end-to-end communication rates that must be maintained. In pursuit of a solution to this problem, we address topics ranging from the modeling of point-to-point wireless communication to mobility control for connectivity maintenance. Since our focus is on developing solutions to these problems that can be experimentally verified, we also detail the design and implantation of a decentralized testbed for multi-robot research. Experiments on this testbed allow us to determine data-driven models for point-to-point wireless channel prediction, test relative signal-strength-based localization methods, and to verify that our algorithms for mobility control maintain the desired instantaneous rates when routing through the wireless network. The tools we develop are integral to the fielding of teams of robots with robust wireless network capabilities
A robot swarm assisting a human fire-fighter
Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
DOOR-SLAM: Distributed, Online, and Outlier Resilient SLAM for Robotic Teams
To achieve collaborative tasks, robots in a team need to have a shared
understanding of the environment and their location within it. Distributed
Simultaneous Localization and Mapping (SLAM) offers a practical solution to
localize the robots without relying on an external positioning system (e.g.
GPS) and with minimal information exchange. Unfortunately, current distributed
SLAM systems are vulnerable to perception outliers and therefore tend to use
very conservative parameters for inter-robot place recognition. However, being
too conservative comes at the cost of rejecting many valid loop closure
candidates, which results in less accurate trajectory estimates. This paper
introduces DOOR-SLAM, a fully distributed SLAM system with an outlier rejection
mechanism that can work with less conservative parameters. DOOR-SLAM is based
on peer-to-peer communication and does not require full connectivity among the
robots. DOOR-SLAM includes two key modules: a pose graph optimizer combined
with a distributed pairwise consistent measurement set maximization algorithm
to reject spurious inter-robot loop closures; and a distributed SLAM front-end
that detects inter-robot loop closures without exchanging raw sensor data. The
system has been evaluated in simulations, benchmarking datasets, and field
experiments, including tests in GPS-denied subterranean environments. DOOR-SLAM
produces more inter-robot loop closures, successfully rejects outliers, and
results in accurate trajectory estimates, while requiring low communication
bandwidth. Full source code is available at
https://github.com/MISTLab/DOOR-SLAM.git.Comment: 8 pages, 11 figures, 2 table
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