We gratefully acknowledge our funding resources:

  • National Science Foundation (NSF)
  • Sandia National Laboratory (SNL)
  • National Aeronautics and Space Administration (NASA)
  • New Mexico Space Grant Consortium (NMSGC)

Distributed Resource/Task Allocation for Multi-Agent Systems in Dynamic Environments

The task/resource allocation problem is an integral part of combinatorial optimization, which has wide applicability for multi-agent decision making and coordination. In cooperative multi-agent systems, task allocation algorithms often form building blocks for more complex problems and have been widely investigated in the literature. Of significant challenges in a general task allocation problem is when the number of agents (m) is not equal to the number of tasks (n), i.e., m ≠ n. In this research project, we are exploring different paths in parallel to provide distributed algorithms for general task allocation problems where the system dynamics and environments are time-varying with uncertainty. 

Autonomous Distribute Cooperative Tracking for Multiple Mobile Ground Targets Using Multiple UAVs


Lab testing of Crazyflie Nana drones

Tethered Heterogeneous Unmanned Aerial and Ground System (THUAGS)

THUAGS is an innovative autonomous robotic platform that offers secure, persistent, reliable, and autonomous solutions to utility inspection, precision agriculture, search and rescue, telecommunication, traffic monitoring, news gathering, defense, and private and public safety. In theory, software simulations, and experimental tests, THUAGS has shown its effectiveness in collaboration between the aerial and ground vehicles for self-localization, coordination, and control using onboard IMU sensors. The tether allows the system to have a focal point of flight navigation, receive uninterrupted flight control, power, and data transmission, and ensures that errant losses of the signal will not cause a pilot to lose control of a traditional drone.

Lab testing of a tethered drone with a power box.

Flight testing in the Activity Center at NMSU.

Bio-Inspired Sound Source Localization Using a Self-Rotating Bi-Microphone Array

Mainstream technologies for object localization are based on computer vision, supported by visual sensors (e.g., cameras), which, however, are subject to lighting and line-of-sight conditions and rely on computationally demanding image-processing algorithms. An acoustic sensor (e.g., a microphone), as a complementary component in a robotic sensing system, does not require a line of sight and is able to work under varying light (or completely dark) conditions in an omnidirectional manner. Thanks to the advancement of microelectromechanical technology, microphones become inexpensive and do not require significant power to operate. In this research project, we are exploring innovative techniques that perform both orientation and distance localization of sound sources in a three-dimensional (3D) space using only the inter-channel time difference (ICTD) cues, generated by a novel self-rotational bi-microphone robotic platform.

Lab testing of localizing four sound sources in ASL.

Measurements and localization result of an experiment in ASL.

Safe Operation of Collaborative Unmanned Aerial Systems in Challenging Environments

Safe operation of a large number of UAS/drones in an urban environment is challenging as the GPS signal may be downgraded or unavailable and the unsteady airwakes behind a high-rise building can be vital those aerial robots. This research project aims to (1) establish the relative kinematics of neighboring UAVs based on a local-level coordinate frame, (2) derive the control law that drives a UAV to maintain a three-dimensional formation with respect to its neighboring UAVs, and (3) estimate the wind profile using the relative kinematics.

Simulation of two UAVs maintaining a 3D formation in a GPS-denied environment.

Dynamic Exhaustive Mobile Target Search Using Collaborative Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) have been used in exploration and searching problems, which have benefited research in areas such as intelligence, surveillance, and reconnaissance (ISR), disaster analysis, search and rescue, weather analysis, law enforcement, and wildlife management. Searching for mobile targets in a specified area using collaborative UAVs is a challenging problem due to the limited sensing range of UAVs and the uncertainty in target states. This research aims to develop a path-planning approach to command and control a team of UAVs to perform exhaustive search on mobile targets.

Dynamics of a confidence area.

The confidence area built by three collaborative UAVs.

Time evolution of the confidence area built by collaborative UAVs.