Lab for Autonomous and Intelligent Robotics (LAIR)
LAIR is a research laboratory at Harvey Mudd College focused on multi-robot systems, their applications, and related topics such as motion planning, localization, mapping, social systems, and control. The lab conducts international partnerships and expeditions, with funding from NSF, ONR, and other agencies. It aims to advance autonomous systems and robotics research.
Industries
Nr. of Employees
large (251-1000)
Lab for Autonomous and Intelligent Robotics (LAIR)
Products
Automatic Shipwreck Site Detection
Pipeline combining side-scan sonar preprocessing, feature extraction, convolutional neural networks, and classifiers to identify probable shipwreck locations in sonar imagery.
AUV-Magnetometer Survey Methods
Methods and field-validated procedures for towing a total-field magnetometer from an AUV, synchronously logging magnetic data, and creating probabilistic anomaly maps for wreck detection.
Shark Tracking with AUVs
Multi-AUV system and algorithms for tracking acoustically tagged marine animals, including field deployments and published methodologies for tracking aggregations.
Autonomous Loader autonomy stack
Perception, mapping, and navigation system for an autonomous track loader using LiDAR, GPS, and computer vision to traverse and avoid static and moving obstacles.
AUV Mission Data Assimilation
Techniques and workflows for integrating AUV-collected environmental parameters into regional ocean models and producing high spatial and temporal resolution environmental maps.
Automatic Shipwreck Site Detection
Pipeline combining side-scan sonar preprocessing, feature extraction, convolutional neural networks, and classifiers to identify probable shipwreck locations in sonar imagery.
AUV-Magnetometer Survey Methods
Methods and field-validated procedures for towing a total-field magnetometer from an AUV, synchronously logging magnetic data, and creating probabilistic anomaly maps for wreck detection.
Shark Tracking with AUVs
Multi-AUV system and algorithms for tracking acoustically tagged marine animals, including field deployments and published methodologies for tracking aggregations.
Autonomous Loader autonomy stack
Perception, mapping, and navigation system for an autonomous track loader using LiDAR, GPS, and computer vision to traverse and avoid static and moving obstacles.
AUV Mission Data Assimilation
Techniques and workflows for integrating AUV-collected environmental parameters into regional ocean models and producing high spatial and temporal resolution environmental maps.
Services
Joint research projects, field trials, and expedition support for autonomous vehicle deployments and environmental sensing.
Design and implementation of machine-learning models, motion-planning algorithms, and task-allocation systems for multi-robot teams.
Integration of marine sensors with autonomous platforms and development of calibration curves and filters for reliable interpretation of measurements.
Processing and assimilation of AUV/ASV-collected environmental sensor data into spatial and spatiotemporal models (e.g., dissolved oxygen, currents).
Joint research projects, field trials, and expedition support for autonomous vehicle deployments and environmental sensing.
Design and implementation of machine-learning models, motion-planning algorithms, and task-allocation systems for multi-robot teams.
Integration of marine sensors with autonomous platforms and development of calibration curves and filters for reliable interpretation of measurements.
Processing and assimilation of AUV/ASV-collected environmental sensor data into spatial and spatiotemporal models (e.g., dissolved oxygen, currents).
Expertise Areas
- Multi-robot systems and coordination
- Autonomous underwater and surface vehicles
- Machine learning for remote sensing and imagery
- Probabilistic state estimation and data assimilation
Key Technologies
- Autonomous underwater vehicles (AUVs)
- Autonomous surface vehicles (ASVs)
- Multi-rotor aerial vehicles (quadcopters)
- Side-scan sonar image processing
News & Updates
7/12/2018 - Shark Tracking Paper Accepted to IROS 2018
The 2018 Shark Tracking team's paper "Acoustic Tag State Estimation with Unsynchronized Hydrophones on AUVs" was accepted to 2018 International Conference on Intelligent Robots and Systems (IROS) in Madrid.
7/1/2018 - Book Chapter on Shark Tracking published!
Prof. Clark co-authored a book chapter, "Use of Autonomous Vehicles for Tracking and Surveying of Acoustically Tagged Elasmobranchs" with CSU Long Beach's Prof. Chris Lowe in _Shark Research: Emerging Technologies and Applications for the Field and Laboratory_.
5/15/2018 - LAIR Class of 2018 Moving On!
In May of 2018, eight students graduated from the LAIR to move on to bigger and better things, including pursuing graduate studies at various universities and joining industry.
7/12/2018 - Shark Tracking Paper Accepted to IROS 2018
The 2018 Shark Tracking team's paper "Acoustic Tag State Estimation with Unsynchronized Hydrophones on AUVs" was accepted to 2018 International Conference on Intelligent Robots and Systems (IROS) in Madrid.
7/1/2018 - Book Chapter on Shark Tracking published!
Prof. Clark co-authored a book chapter, "Use of Autonomous Vehicles for Tracking and Surveying of Acoustically Tagged Elasmobranchs" with CSU Long Beach's Prof. Chris Lowe in _Shark Research: Emerging Technologies and Applications for the Field and Laboratory_.
5/15/2018 - LAIR Class of 2018 Moving On!
In May of 2018, eight students graduated from the LAIR to move on to bigger and better things, including pursuing graduate studies at various universities and joining industry.