Current Projects (select):
Collaborative Research: NRI: Reducing Falling Risk in Robot-Assisted Retail Environments
Multi-Agent Integration with Android Team Awareness Kit
Sponsor: Air Force SBIR, Phase 2 whith Kinnami, Inc.
Data Security Challenges for Multi-Agent Cooperative Robotic Systems Phase 2
StickBug – an Effective Co-Robot for Precision Pollination
WVU Today Press Release
Autonomous Robotic Early Warning System for Underground Stone Mining Safety
Sponsor: Alpha Foundation
Autonomous Navigation of
Small UAS/UGV Teams in Underground Tunnels
See Project Description
Past Projects (select):
Fast Traversing Autonomous Rover for Mars Sample Collection
Sponsor: National Aeronautics and Space Administration (NASA)
Precision Pollination RobotSponsor: USDA NIFA National Robotics Initiative
Multi-Constellation GNSS, Multi-Sensor Precise Point PositioningSponsor: National Geospatial-Intelligence Agency's New Investigator Program
The overall objective in this NGA New Investigator Program project is to design,
develop and demonstrate kinematic positioning software that uses the high-fidelity
of models of precise point positioning and the diversity of multi-GNSS as well
as multi-sensor data (MM-PPP) to offer improved accuracy and robustness over the
current state-of-the-art. Furthermore, novel receiver autonomous integrity monitoring algorithms
that are tailored to the expected accuracy of MM-PPP and leverage multi-sensor
diversity will be designed and implemented. Experimental validation and robustness
will be conducted using a fleet of instrument small unmanned aerial vehicles.
INSIGHTS: Inertial Navigation Systems Integrated into the GIPSY-OASIS for High-Accuracy Tightly Coupled SolutionsSponsor: NASA Jet Propulsion Laboratory
This project is adding an inertial navigation system capability into leveraging JPL's state-of-the-art GNSS processing software, Real-Time GIPSY-X.
PPP is a technique that uses precise GPS orbit and clock solutions and sophisticated models to mitigate common GPS error sources to yield very accurate absolute positioning from data collected with a single GPS receiver that is located anywhere in the world. This approach is different from traditional differential GPS processing techniques, as PPP does not necessitate the use of a GPS reference station. INSIGHTS objective is to update RTG-X to include an inertial navigation system module and experimentally validate its integration through flight tests. This will potentially yield more accurate positioning of mobile platforms while still taking advantage of the global availability of PPP approach.
Improving K-PPP accuracy would in-turn improve the science products of existing Earth-science remote-sensing platforms that require global availability. For example, it could help realize the potential atmospheric science return from ocean-based GPS stations (e.g. buoys and wave gliders) and open small UAVs to science applications that demand high accuracy on-the-fly.
As part of West Virginia's first spacecraft mission, we are integrating and testing the GPS receiver payload. For STF-1 our GPS receiver is the Fast, Orbital, TEC, Observables and Navigation — or FOTON — receiver that was developed by UT-Austin and Cornell and was graciously donated by Dr. Glenn Lightsey. With the FOTON's raw GPS observables, we are seeking to advance that state-of-the-art precise orbit determination on the CubeSat platform. Our GPS post-processing will leverage NASA's GIPSY-OASIS.
Future conflicts in contested environments will require coordination between teams of manned and unmanned platforms performing ISR tasks. Coordinating ISR tasks is much more challenging in these contested conditions as GPS cannot be reliably depended upon. Consider the ISR task of handing off a tracked target from one platform to another. Reliably performing this task requires at a minimum an estimate of the relative pose (change in 3D position and orientation) between the two ISR sensors. In the GPS-enabled case, this is trivial to compute from the current GPS-INS position/attitude estimates on each of the platforms. In the GPS-denied case, however, this task becomes much harder. Under this STTR we propose a joint effort between Systems and Technology Research and academic partner West Virginia University to develop a solution to GPS-denied relative pose estimation. Our proposed approach exploits data from multiple sensors, including imagery and inertial measurements, in a joint fusion framework for modeling and inferring relative pose in the absence of GPS. We will evaluate our approach in the GPS-denied, cross-modal target handoff application, and compare our performance with the traditional GPS-enabled case. BENEFIT: The technology developed on this program provides a statistically sound foundation for establishing a common coordinated frame between two platforms, thus enabling reasoning about coordinated tasks (with uncertainty) without GPS. This has wide applicability to any coordinated military activity in contested environments, including ISR tasks like target hand off as well as joint/cooperative navigation. Similarly, it has non-military application to any coordinated robotics application where GPS is unreliable, such as search-and-rescue.
A Concept Study for the use of Lighter Than Air Vehicles for the Next Generation of Sub-Orbital PayloadsSponsor: NASA WV Space Grant Consortium Joint Univertsity-Industry Program
Very recently, a group of NASA scientists have publicized their interest in the use of large lighter-than-air platforms (e.g. airships, stratospheric balloons, tethered balloons) for use in sub-orbital scientific investigations. Their rationale being that these platforms stand to offer ‘significant gains in observing time, sky and ground coverage, data downlink capability, and continuity of observations over existing suborbital options at competitive prices’. This project will consist of an initial feasibility trade study for the use of LTA platforms to support a specific scientific instrument concept that is under consideration by a group of NASA JPL science collaborators.
Cooperative Gust Sensing and Suppression for Aircraft Formation Flight
The WVU Navigation Lab is participating as an unfunded collaborator on the IRL's NASA LEARN project and will be leading the precise real-time relative navigation algorithm development and implementation.