Decentralized Linear Convoying for Underactuated Surface Craft with Partial State Coupling

This work introduces a novel decentralized algorithm and control law for stable linear convoying using a layered control approach. This algorithm was implemented in MOOS-IvP, using an abstraction layer that models a virtual system decoupled from the system’s actual dynamics. This makes the algorithm platform-agnostic and able to be combined with other behaviors such as collision avoidance and operating region behaviors. A trajectory defined by a lead agent is discretized and embedded with the leader’s dynamics and propagated to all following agents. We first demonstrate that this approach when paired with a simple PD controller prevents accumulated errors and improves trajectory tracking for follower agents. Thereafter we demonstrate how virtually coupling a subset of agent states improves the overall cohesiveness of the convoy. Improvements are demonstrated in both simulations and field trials using five autonomous surface vehicles.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802418
Citations
1
Primary Topic
Dynamics and Control of Mechanical Systems
Type
article
Field-Weighted Citation Impact
0.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Decentralized Linear Convoying for Underactuated Surface Craft with Partial State Coupling

Michael R. Benjamin, Raymond Turrisi
1 citations
Dynamics and Control of Mechanical Systems
0.33
article

Decentralized Linear Convoying for Underactuated Surface Craft with Partial State Coupling

Michael R. Benjamin, Raymond Turrisi
article en
1 citations

Abstract

This work introduces a novel decentralized algorithm and control law for stable linear convoying using a layered control approach. This algorithm was implemented in MOOS-IvP, using an abstraction layer that models a virtual system decoupled from the system’s actual dynamics. This makes the algorithm platform-agnostic and able to be combined with other behaviors such as collision avoidance and operating region behaviors. A trajectory defined by a lead agent is discretized and embedded with the leader’s dynamics and propagated to all following agents. We first demonstrate that this approach when paired with a simple PD controller prevents accumulated errors and improves trajectory tracking for follower agents. Thereafter we demonstrate how virtually coupling a subset of agent states improves the overall cohesiveness of the convoy. Improvements are demonstrated in both simulations and field trials using five autonomous surface vehicles.

Massachusetts Institute of Technology (US)
Climate action
Openalex Percentile: Top 38%
Dynamics and Control of Mechanical Systems
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.