Invention Description Navigating complex and obstacle-rich environments is a major challenge for unmanned aerial vehicles (UAVs), especially in spaces where GPS signals are unavailable or prior environmental maps do not exist. Traditional drones are highly vulnerable to collisions, which can disrupt navigation, damage hardware, and limit their effectiveness...

Invention Description Long-range imaging systems are often affected by atmospheric turbulence, which can introduce blur, distortion, and reduced image quality. Traditional turbulence simulators typically ignore depth-dependent variations, limiting their ability to accurately represent real-world imaging conditions. This lack of realism can hinder the...

Invention Description Concentrated Solar Power (CSP) systems increasingly rely on real-time data aggregation through advanced communication frameworks such as Over-the-Air Computation (AirComp) in emerging 6G-IoT environments. However, these systems are vulnerable to signal interference and jamming attacks, which can disrupt data transmission and compromise...

Invention Description Long-range image analysis presents a significant challenge in computer vision, primarily due to atmospheric turbulence. The spatiotemporal variation in the medium's refractive index causes light ray bending, resulting in image degradation, specifically blurring and geometric deformation. Traditional estimation methods for...

Invention Description Retrieval-Augmented Generative (RAG) models boost generative AI’s accuracy by connecting large language models (LLMs) with the most current, external, knowledge sources. RAG models are widely used in fact-checking, information retrieval, and AI-driven search engines. Despite their utility, adversarial threats can exploit...

Invention Description Detecting bright point scatterers is important to quality assessments of sonar, radar and medical imaging systems, particularly as it pertains to resolution characterization. Prominent, or coherent, scatterers are typically detected using thresholding techniques in addition to statistical measures in the detection processing chain....

Invention Description UAVs rely on fiducial markers, such as AprilTag or Aruco, to help with navigation and precision landing under GPS-denied environments. However, these markers are facing significant limitations in dense urban environments from adverse weather conditions, low visibility, urban clutter as well as security risks from tampering. These...

Continuous-time reinforcement learning (CT-RL) algorithms hold great promise in real-world control applications. Adaptive dynamic programming (ADP)-based CT-RL algorithms, especially their theoretical developments, have achieved great successes. However, these methods have not been demonstrated for solving realistic or meaningful learning control problems....

Event-based cameras that asynchronously detect changes in pixel brightness with high temporal resolution, high dynamic range, and low-power, have been very successful for robotic vision and autonomous navigation. Depth estimation from monocular or stereo event cameras is an important task which helps improve downstream robotic localization and mapping...

This algorithm is developed in the field of control systems for control of affine nonlinear continuous time (CT) systems, which include important application areas such as robotics and autonomous systems, aerospace, manufacturing, and process control. This invention falls under the class of continuous-time reinforcement learning (CT-RL) control algorithms....