Revisiting End-to-end Deep Learning for Obstacle Avoidance: Replication and Open Issues.
Alexander K. SeewaldPublished in: ICAART (2) (2020)
Keyphrases
- end to end
- open issues
- deep learning
- obstacle avoidance
- mobile robot
- path planning
- unsupervised learning
- unsupervised feature learning
- machine learning
- congestion control
- visually guided
- motion planning
- ad hoc networks
- mental models
- weakly supervised
- dynamic environments
- multi robot
- object recognition
- feature extraction