Model-free source seeking control for cluttered GPS-denied environments with nonconvex signal fields

Abstract

Research problem- This project addresses grand challenges in long-range detection resulting from the limitations of centralized sensing systems (employed in unmanned vehicles) in dealing with complex signal fields in real-life congested environments. Regardless of the quantity or sensitivity of the sensors used, reliable sensing in these environments remains unattainable due to strong influence of the environment on signals propagation paths leading to multi-path signals, signal distortion, and degradation. These challenges stem from the failure of current perception techniques in fully leveraging the vehicle s mobility to actively explore the environment and autonomously address ambiguities in the measured signals. Objectives- The objective of this project is to develop model-free real-time adaptive sensing and navigation frameworks that enable autonomous exploration of uncertain dynamic environments where measured signals are distorted, diverted, or diffused by environmental factors. The control strategies will safely steer multiple surface and underwater vehicles to the location of static or moving signal sources, without knowledge of their position or the position of the sources. Technical approaches- The proposed approach utilizes a r an g e o f model- free optimization methods to enable localizing precise global signal optima, aka the signal sources, in spatially distributed nonconvex fields. The frameworks enable multi-source localization and multi-vehicle operation and include online safety and collision avoidance components to guarantee safe navigation in dynamic and cluttered environments. The prescribed time components allow converging to the source in user-defined convergence time, independent of initial conditions and other parameters, within the physically allowable range. The work entails both theoretical and operational frameworks to enable robust open-world application of the seekers and will provide mathematical proof of stability for the designedcontrol to ensure desired behavior in the presence of uncertainties. Anticipated outcomes: The outcome is a perception system that guarantees robust performance in dynamic and unpredictable settings, offering the following advantages: (1) powerefficiency by developing a systematic computationally low-cost search methodology and providing the versatility to use a single sensor, obviating the necessity for intricate arrays or distributed sensory systems; (2) integrated strategies for addressing signal interference and degradation within the control scheme; (3) novel safety mechanisms that strike a balance between conservativeness andperformance; (4) position-free operation; (5) multi-source localization and multi-vehicle operation; (6) provision of coordination-free and limited coordination operation options for multi-vehicle cases to address challenges associated with sensing/estimating other vehicle states or communication in demanding environments; and (7) convergence to the source in user-prescribed time (within thephysically allowable range). Impact on DoD capabilities- The ability to navigate towards signals emitted by points of interest in complex and unpredictable environments finds diverse applications, encompassing underwater vehicle/asset deployment and recovery, search and rescue missions, maritime reconnaissance, and marine environmental monitoring. These applications hold significant relevanceto naval operations, with one particularly crucial application being anti-submarine warfare (ASW). Traditional ASW technologies involve complex and cost-prohibitive processes and platforms. The proposed frameworks enable a network of unmanned autonomous vehicles to locate a single or multiple adversary submarines offering advantages such as affordability, scalability, reduced detectability, and sufficient redundancy to overwhelm the adversaries. The frameworks enable detection using any measurable signal in GPS-denied environments.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 11, 2024
Source ID
N000142412269

Entities

People

  • Zahra Nili Ahmadabadi

Organizations

  • Office of Naval Research
  • Salk Institute for Biological Studies
  • United States Navy

Tags

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Robotics and Automation.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers