A Deep Reinforcement Learning-based Application Framework for Conveyor Belt-based Pick-and-Place Systems using 6-axis Manipulators under Uncertainty and Real-time Constraints.
Tuyen Pham LeDonghyun LeeDaeWoo ChoiPublished in: UR (2021)
Keyphrases
- real time
- reinforcement learning
- distributed systems
- expert systems
- main contribution
- intelligent systems
- telecommunication systems
- autonomous mobile
- function approximation
- low cost
- management system
- software engineering
- semi supervised
- theoretical framework
- complex systems
- constraint satisfaction
- constraint programming
- probabilistic model
- information systems
- machine learning