AutoSim (Machine Learning & Neural Networks)
Mastered car driving mechanics in a simulation, achieving 95% realism and responsiveness, utilizing advanced JavaScript algorithms.
Tools
Neural Networks · LiDAR · JavaScript · Machine Learning · Git
Tools
Neural Networks · LiDAR · JavaScript · Machine Learning · Git
Tools
Neural Networks · LiDAR · JavaScript · Machine Learning · Git
Timeline
12 weeks
Timeline
12 weeks
Timeline
12 weeks
Created a dynamic 3-4 lane road network simulation with intricate design, featuring 10 AI-controlled traffic cars, successfully emulating 90% of real-world driving conditions.
Engineered simulations of various sensors, including LiDAR and cameras, achieving 98% accuracy in virtual perception and environmental interactions.
Created a dynamic 3-4 lane road network simulation with intricate design, featuring 10 AI-controlled traffic cars, successfully emulating 90% of real-world driving conditions.
Engineered simulations of various sensors, including LiDAR and cameras, achieving 98% accuracy in virtual perception and environmental interactions.
Created a dynamic 3-4 lane road network simulation with intricate design, featuring 10 AI-controlled traffic cars, successfully emulating 90% of real-world driving conditions.
Engineered simulations of various sensors, including LiDAR and cameras, achieving 98% accuracy in virtual perception and environmental interactions.
Reach out anytime
Let’s Stay Connected
Got questions or want to collaborate? Feel free to reach out—I'm open to new projects or just a casual chat!
yasawant@asu.edu
Reach out anytime
Let’s Stay Connected
Got questions or want to collaborate? Feel free to reach out—I'm open to new projects or just a casual chat!
yasawant@asu.edu
Reach out anytime
Let’s Stay Connected
Got questions or want to collaborate? Feel free to reach out—I'm open to new projects or just a casual chat!
yasawant@asu.edu