Development of an Adaptable Communication Layer with QoS Capabilities for a Multi-Robot System

Harms, Hans-Heinrich; Schmiemann, J.; Schattenberg, Jan; Frerichs, Ludger

doi:10.1007/978-3-319-70836-2_64

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…Since all messages are now routed through a single node, traffic shaping can be readily implemented. While independently conceived and implemented, udp_mesh improves upon the Pound (Harms et al, 2017) 3 package by adding additional quality-of-life services such as name resolution and removing a requirement that topics and priorities need to be declared at compile time. Other competitors faced similar limitations with bandwidth and the ROS networking stack.…”

Section: Udp-mesh Based Communicationsmentioning

confidence: 99%

Multi-Agent Autonomy: Advancements and Challenges in Subterranean Exploration

Ohradzansky

Riley

et al. 2022

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Artificial intelligence has undergone immense growth and maturation in recent years, though autonomous systems have traditionally struggled when fielded in diverse and previously unknown environments. DARPA is seeking to change that with the Subterranean Challenge, by providing roboticists the opportunity to support civilian and military first responders in complex and high-risk underground scenarios. The subterranean domain presents a handful of challenges, such as limited communication, diverse topology and terrain, and degraded sensing. Team MARBLE proposes a solution for autonomous exploration of unknown subterranean environments in which coordinated agents search for artifacts of interest. The team presents two navigation algorithms in the form of a metric-topological graph-based planner and a continuous frontier-based planner. To facilitate multi-agent coordination, agents share and merge new map information and candidate goal points. Agents deploy communication beacons at different points in the environment, extending the range at which maps and other information can be shared. Onboard autonomy reduces the load on human supervisors, allowing agents to detect and localize artifacts and explore autonomously outside established communication networks. Given the scale, complexity, and tempo of this challenge, a range of lessons was learned, most importantly, that frequent and comprehensive field testing in representative environments is key to rapidly refining system performance.

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Section: Udp-mesh Based Communicationsmentioning

confidence: 99%

Multi-Agent Autonomy: Advancements and Challenges in Subterranean Exploration

Ohradzansky

Riley

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Since all messages are now routed through a single node, traffic shaping can be readily implemented. While independently conceived and implemented, udp mesh improves upon the Pound (Harms et al, 2017) 3 package by adding additional quality-of-life services such as name resolution and removing a requirement that topics and priorities need to be declared at compile time. Other competitors faced similar limitations with bandwidth and the ROS networking stack.…”

Section: Udp-mesh Based Communicationsmentioning

confidence: 99%

Multi-Agent Autonomy: Advancements and Challenges in Subterranean Exploration

Ohradzansky¹,

R.²,

Riley³

et al. 2021

Preprint

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Artificial intelligence has undergone immense growth and maturation in recent years, though autonomous systems have traditionally struggled when fielded in diverse and previously unknown environments. DARPA is seeking to change that with the Subterranean Challenge, by providing roboticists the opportunity to support civilian and military first responders in complex and high-risk underground scenarios. The subterranean domain presents a handful of challenges, such as limited communication, diverse topology and terrain, and degraded sensing. Team MARBLE proposes a solution for autonomous exploration of unknown subterranean environments in which coordinated agents search for artifacts of interest. The team presents two navigation algorithms in the form of a metric-topological graph-based planner and a continuous frontier-based planner. To facilitate multi-agent coordination, agents share and merge new map information and candidate goal-points. Agents deploy communication beacons at different points in the environment, extending the range at which maps and other information can be shared. Onboard autonomy reduces the load on human supervisors, allowing agents to detect and localize artifacts and explore autonomously outside established communication networks. Given the scale, complexity, and tempo of

show abstract