PROJECT: Real-time Generative AI Motion-Planning with Safety Guarantees
Broad Problem: End-to-end real-time motion planning and control of autonomous agents via generative AI.
Key Challenges: Motion trajectories that satisfy fundamental constraints and guarantees (e.g., safety, stability, collision-avoidance) are difficult to generate with AI methods, especially while making it computationally efficient enough to run in real-time.
Research Goal: Develop planning algorithms for autonomous agents in various complex scenarios while maintaining fundamental constraints and guarantees (e.g., safety, stability, collision-avoidance), by combining both generative AI and traditional planning methods.
Application Areas: Robotics; Autonomous driving; Wheeled mobile robots; Robot Arm Manipulation.