LCM: Lightweight Communications and Marshalling

By Albert S. Huang, Edwin Olson, David C. Moore. 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

375 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Control and Systems Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/680b4c4a3f9a1e2444930e86d772c8e214123e4b

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In Aerospace Engineering

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Citations in the corpus

PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision (2012, methodology): “We rely on the Lightweight Communication Marshalling library (LCM) as the base middleware, as it was shown in [15] that LCM outperforms ROS in low-latency applications.”
Pushbroom stereo for high-speed navigation in cluttered environments (2014, methodology): “A second ODROID-U2, communicating over LCM [18], runs our state-estimatator (a 12-state Kalman filter from [7]) and connects to our low-level interface, a firmware-modified APM 2.”
Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior (2022, methodology): “We implement an interface based on Lightweight Communications and Marshalling (LCM) [28] to pass sensor data, motor commands, and joystick state between our code and the low-level control SDK provided by Unitree.”
Robot Operating System 2: Design, architecture, and uses in the wild (2022, background): “It concentrates on handling messaging and data marshalling in high-bandwidth low-latency environments [20].”
Toward Interactive Grounded Language Acqusition (2013, background): “Low-level communication is handled by LCM [8] and ROS [22].”
PX4: A node-based multithreaded open source robotics framework for deeply embedded platforms (2015, background): “Huang et al. created a publish-subscripe design pattern object request broker for robotics systems [1] which is particularly lightweight and low latency.”
Baxter's Homunculus: Virtual Reality Spaces for Teleoperation in Manufacturing (2017, background): “Lightweight Communications and Marshalling (LCM), developed by MIT and University of Michigan proved a sufﬁcient solution [19].”
Visual-Inertial Navigation Algorithm Development Using Photorealistic Camera Simulation in the Loop (2018, methodology): “The system uses Lightweight Communications and Marshaling (LCM) [31] for communication between on-board modules, giving a lightweight and ﬂexible framework.”