MANIPULATION
A Deep Reinforcement Learning Algorithm for Robotic Manipulation Tasks in Simulated Environments
Carlos Calderón, Roger Sarango
- Year
- 2023
- Citations
- 3
- Access
- Open access
Abstract
Industrial robots are used in a variety of industrial process tasks, and due to the complexity of the environment in which these systems are deployed, more robust and accurate control methods are required.
Keywords
Reinforcement learningComputer scienceTask (project management)RobotRobot end effectorPosition (finance)Process (computing)Artificial intelligenceMotion (physics)Work (physics)
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 cites
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002