Enhancing Pilot Training: Empowering AI for Adaptive Learning Applications

Transforming eVTOL Training with Data Insights

Electric Vertical Take-Off and Landing (eVTOL) aircraft represent cutting-edge technology that offers a sustainable mode of transportation. As the aviation industry encounters significant workforce shortages due to cost, time, and limited access to training resources, innovative solutions are essential. 

Systems Technology, Inc. (STI) and AI Redefined (AIR) formed a strategic partnership to redefine eVTOL training with a data-driven approach. This collaboration focuses on leveraging data insights to improve training processes, reduce time and costs, optimize efficiency, and ensure compliance with safety regulations. AIR’s Cogment Adaptive Learning platform utilizes artificial intelligence to analyze learner performance, deliver personalized feedback, and create tailored training materials. 

By integrating simulation-based training with AI insights, this platform empowers learners to experience flexible, self-paced training. This shift from traditional time-based models to performance-based assessment maximizes learning outcomes and ensures that the training programs meet the industry’s dynamic needs.

The Rise of Electric Vertical Take-Off and Landing (eVTOL) Aircraft

By 2050, it is projected that two-thirds of the world’s population will live in urban areas. With the anticipated increase in the demand for better transportation systems, eVTOL aircraft present an innovative solution. Establishing flexible transit routes, they help the passengers to avoid traffic congestion while operating with minimal noise and emissions.

However, the industry simultaneously confronts critical workforce shortages in aviation. By 2028, approximately 60,000 fully qualified pilots will be needed to support aggressive growth targets for this industry. This highlights the urgent need for efficient, adaptable training solutions that can effectively educate the future workforce.

Driving eVTOL Training Innovation with AI Redefined (AIR)

In November 2023, STI and AIR announced a key partnership focused on improving training for eVTOL aircraft. With over 65 years of expertise in dynamics and controls, STI has been a trusted partner to industry leaders, including NASA, the FAA, and the U.S. Department of Defense.

This partnership aims to redefine the training landscape for pilot training by integrating adaptive learning technologies with artificial intelligence and sophisticated simulation tools. The goal is to provide pilots with an immersive, realistic training environment that reinforces skills development through tailored feedback and targeted content recommendations.

Advancing Training with Cogment Adaptive Learning

The Cogment Adaptive Learning platform seamlessly integrates with simulation-based learning environments to deliver personalized training experiences. 

As students participate in flight simulation exercises, the platform leverages artificial intelligence to analyze performance, provide constructive feedback, and generate customized training materials tailored to individual needs. This approach enhances skill development and training efficiency. 

AIR and STI collaborated to develop a proof of concept using Cogment Adaptive Learning for eVTOL pilot training, specifically focusing on the hover-to-land maneuver. This simulation is fully integrated with a piloted flight simulator, offering a realistic training scenario. The platform facilitates learning by: 

  1. Assessing performance and providing actionable feedback.
  1. Recommending new content to target areas needing additional practice.

Optimizing Learning with AI-Driven Performance Feedback

During simulation exercises, the AI-Evaluator monitors student performance to provide assessment and feedback in real-time. This AI-driven system compares student performance against a benchmark to determine optimal task execution, identifying deviations from desired performance. It offers both qualitative and quantitative feedback.

Key Features: 

  1. Online coaching support: Real-time feedback to correct behaviors that lead to errors.

  1. Offline replay and debriefing: Comprehensive review of the entire training session, including detailed performance summaries and areas needing improvement.
  1. Origin of error analysis: Investigation of behaviors leading to errors, providing insights into error origins and consequences.

Tailored Practice Recommendations for Skill Enhancement

The AI-Director utilizes insights from the AI-Evaluator to guide its recommendations for targeted practice sessions for improving specific skill areas. Leveraging feedback from previous exercises, the AI-Director suggests content for the next session, focusing on areas where challenges were identified. These recommendations include adjusting task parameters such as skills and techniques to practice, environmental conditions, and the level of guidance provided by the Evaluator.

Benefits of Using Cogment Adaptive Learning for Training

The Cogment Adaptive Learning platform allows students to learn at their own pace, identifying challenging areas and receiving feedback. Rather than replacing instructors, this platform streamlines one-on-one interactions, which enables more efficient review of lessons and delivering insights at a deeper level.

Key Advantages:

  1. Customized learning paths: Automatically adjusts training content to target individual weaknesses, providing diverse scenarios for skill development.
  1. Enhanced learning outcomes: Focused on creating personalized content that improves competency development, which boosts student retention rates and overall learning outcomes.
  1. Optimized instructor time: Allows instructors to focus on areas that need the most attention.
  1. Cost efficiency: Reduces the cost associated with developing educational content by automatically generating scenarios and validating them with instructors.
  1. Advanced data management: Facilitates comprehensive data management, including scenario generation, student performance metrics, and tracking training progress.

Advancing Training Through Cogment Adaptive Learning

The initial evaluations of the Cogment Adaptive Learning eVTOL training system have demonstrated promising results, highlighting key advantages of data-driven approaches. Pilots participating in limited trials using simulation for landing tasks have provided valuable feedback, suggesting enhancements in user interface design, evaluation methods, and student feedback mechanisms. 

STI and AIR are currently expanding the platform with diverse training modules covering the entire spectrum of eVTOL pilot training. This includes systems and procedures learning, specific maneuvers, and comprehensive flight missions. This ongoing development highlights our dedication to shaping the future of aviation training.

Elevate Your Training Experience Today

Discover the future of pilot training with our Cogment Adaptive Learning platform. Leverage the power of artificial intelligence to enhance your skills and prepare for the next era of flight. 

Schedule a consultation with our team to learn how you can improve your pilot training: https://www.systemstech.com/contact/.

About Systems Technology Inc.: Systems Technology Inc. (STI) is a technology company at the forefront of innovation, specializing in aviation and simulation solutions. With a mission to advance safety and efficiency in aviation, STI develops cutting-edge technologies to meet the evolving needs of the aerospace industry.

About AI Redefined: AI Redefined is a leading applied artificial intelligence research firm dedicated to enabling human-AI alignment. The company focuses on developing RLHF solutions for various industries, including aviation, renewable energy, healthcare, and autonomous (human-machine teaming) systems, with a commitment to driving progress through innovation.

Systems Technology Inc. and AI Redefined Join Forces to Develop World’s First eVTOL Pilot Training Simulator

Oct 30, 2023 – Los Angeles, CA

A generic electric vertical take off and landing aircraft flying high off the ground through a valley over a wide river with mountains of either side as the sun is just rising / setting. The eVTOL is white and has two front and two rear rotors.

Systems Technology, Inc., (STI), a leader in aerospace controls and simulated training assessment for more than 65 years, known for guidance & controls expertise to NASA, FAA, the US Department of Defense and other significant aerospace industry players, is thrilled to announce a strategic partnership with AI Redefined (AIR), a pioneer in applied artificial intelligence products using Reinforcement Learning from Human Feedback (RLHF), to develop the world’s first Electric Vertical Takeoff and Landing (eVTOL) pilot training simulation tool.

The partnership between STI and AIR aims to revolutionize the training landscape for eVTOL pilots by harnessing the power of advanced artificial intelligence (adaptive learning) and state-of-the-art simulation technology. As electric vertical takeoff and landing aircraft become increasingly prevalent in the aviation industry, the need for effective, efficient, and dynamic training solutions has never been more critical.

This groundbreaking simulation tool will provide eVTOL pilots with a highly immersive and realistic training experience, allowing them to hone their skills in a safe and controlled environment. The tool will incorporate multi-agent reinforcement learning (MARL) algorithms with continuous human feedback to simulate a wide range of flight scenarios, including emergency situations, adverse weather conditions, and complex airspace interactions.

Key features of the eVTOL pilot training simulation tool will include:

●      Realistic eVTOL aircraft models

●      Dynamic weather and environmental simulations

●      Interactive and dynamic training scenarios

●      Performance analysis, real time curriculum iterations and feedback

●      Integration with eVTOL control systems



“We are excited to partner with AI Redefined to develop this innovative eVTOL pilot training simulation tool,” said Sanjeev Weerasuriya, CEO of STI.  “As the aviation industry evolves with the introduction of eVTOL aircraft, we are committed to ensuring that pilots receive the highest quality training. This tool will empower eVTOL pilots to navigate the complex skies with confidence and safety.”

Craig Vachon, CEO of AI Redefined, added:

Our expertise in MARL with continuous human feedback, combined with STI’s expertise in aviation technology, positions us perfectly to create a training tool that will scale as a new standard for eVTOL pilot training. This is a fast-growing industry that cannot train new pilots using traditional methods–one-to-one teacher to student. We are excited to contribute to the advancement of this complex and transformative industry.”

The collaboration between STI and AIR represents a significant step forward in the field of eVTOL pilot training. The companies plan to unveil the eVTOL pilot training simulation tool at an industry event in the coming months.

About Systems Technology Inc.: Systems Technology Inc. (STI) is a technology company at the forefront of innovation, specializing in aviation and simulation solutions. With a mission to advance safety and efficiency in aviation, STI develops cutting-edge technologies to meet the evolving needs of the aerospace industry.

About AI Redefined: AI Redefined is a leading applied artificial intelligence research firm dedicated to enabling human-AI alignment. The company focuses on developing RLHF solutions for various industries, including aviation, renewable energy, healthcare, and autonomous (human-machine teaming) systems, with a commitment to driving progress through innovation.

Dave Ward Memorial Lecture Award

STI’s Brian Danowsky recently received the Dave Ward Memorial Lecture Award that is given annually by the Aerospace Control and Guidance Systems Committee to young researchers that have made significant contributions in the areas of guidance and control. Brian was honored for his ongoing work concerning the development of real-time methods to suppress adverse aerolastic modes. Continue reading