Multi-View Perception and Uncertainty Fusion for Autonomous Robots
Type of Project: Robotics Research
Status: Ongoing Research
Summary:
This is an ongoing research project focusing on multi-view perception and uncertainty quantification for autonomous robotic systems. Due to the active nature of this research, detailed information cannot be made public at this time.
Project Overview
The project explores novel approaches to perception fusion from multiple viewpoints while maintaining rigorous uncertainty guarantees for safe autonomous operation. The work involves NVIDIA Isaac Sim for simulation and validation, with live deployment on real robotic platforms.
Project images coming soon
Technical Stack
- Deep Learning Framework: TensorFlow
- Simulation: NVIDIA Isaac Sim
- Sensors: RGB-D cameras
- Focus Areas: Uncertainty Guarantees, Live Deployment
- Application: Autonomous Robotic Systems
More details will be shared upon project completion and publication.