Research topics
Machine Learning for Self-driving vehicles and Smart Mobility
Machine Learning for Self-driving vehicles and Smart Mobility
1. Perception in self-driving vehicles
- Deep learning-based Sensor Fusion
- Multi-modal Object detection(using LIDAR, camera, radar and sound sensors)
- Radar-Camera sensor fusion
- LIDAR-Camera sensor fusion
- Deep learning-based 3D object detection
- LIDAR Object detection
- Camera-based 3D Object detection
- Sensor's for Self-driving environment
- Calibration methods for sensors
- Sensor configuration optimization
- Higher attribute classification/recognition
- Target object Intention decision making
- Trajectory estimation
- Mobility/Traffic rare event detection
2. Dataset generation and improvement for self-driving vehicle and mobility applications
- Domain adaptation
- Knowledge distillation
- Generative models
3. SLAM (Simultaneous Localization and Mapping)
- Localization (Vehicle pose estimation)
- LIDAR odometry using Deep learning
- Map updates using multi measured vehicles
- Spatial AI
4. Decision making using Reinforcement Learning
- Stop and Go problems
- Lane change problems
- Pedestrian vague crossing problems