Unlocking Physics, Engineering and Manufacturing through Competitive Machine Learning Simulations and Performance Assessments
Engage students with Drone WOLF AI (DWA). Apply physics to automate robotics that perform missions: first in the classroom, then in the field.
DWA is a competitive machine learning framework that enhances student’s physics performance and broadens their engineering skills. Using the intuitive ChatGPT interface, students can generate and refine Python code for aerial robotics automation through simple, no-code or low-code physics logic interactions.
DWA Competitive Machine Learning Framework to Enhance Physics Student Performance and Improve Engineering Technology Skills
DWA PHYSICS LABS
Dive Deep into physics by applying concepts like motion, forces, energy, and the electromagnetic spectrum to real-world drone and sensor applications. These labs not only enhance theoretical understanding but also provide practical aerospace engineering experiences. When the drone learns its mission, so too does the student learn physics by the definining and refining the instructions of the mission.
DWA ENGINEERING LABS
Experience engineering first-hand by designing and refining robotic-sensor missions in our simulated online labs. From initial design to real world deployment, each lab is step in mastering real-world scenarios, such as CAD/CAM design and advanced manufacturing. The engineering labs are focused on funded Certifications by Robotics Engineering and Unmanned Safety Institute.
Train Educators
We work with the PhysTEC Society, Industry Experts and engineering educators to create robotics-engineering lab challenges - that align with national science standards and reinforce state/county developed lesson plans - to address the needs of teachers and their student communities. From training on the latest robotics technology to new pedagogical machine learning methods, we help teachers make their classrooms engaging and successful.
Apply and assess the engineering design process (EDP) that encourages open-ended problem solving and learning from failure. While students focus on improving the drone’s mission, educators receive immediate physics learning performance feedback to review areas of weak performance or allow students to advance at their own pace.
Ideate and Assess Student Physics Lab Performance against Lesson Plans
Operate and Monitor Missions in Real Time
Gain access to real time analytics of drone-sensor mission performance
Deploy Innovations from the Cloud to the Field
Utilize the DWA twin technology to allow the ML algorithms developed in the simulated environment to execute on a real airframe in the filed.
Automate Your Missions Effortlessly
Automate by refinining your physics logics to articulate to ChatGPT to translate it to Python code to execute the drone task.
Divide into Lab Teams to tackle physics mission labs, researching and designing machine learning algorithms tailored to the challenge presented.
Design Your Automation Project with Precision
Engage Lab Teams in Search and Rescue Missions where each lab builds upon the last, evolving into your understanding and refining your mission to fly, maneuver, detect and land drones optimizing time and energy more efficiently.
Compete in Mission Critical Scenarios
“Through DWA, students engagement increased exponentially and understanding of the technical concepts were seamless”
Contact
Feel free to contact us with any questions.
Email
info@sofwolf.org
Phone
202.256.3726