Exploring CausalWorld: Enhancing robotic manipulation via knowledge transfer and curriculum learning

arXiv:2403.17266v1 Announce Type: cross
Abstract: This study explores a learning-based tri-finger robotic arm manipulating task, which requires complex movements and coordination among the fingers. By employing reinforcement learning, we train an agent to acquire the necessary skills for proficient manipulation. To enhance the efficiency and effectiveness of the learning process, two knowledge transfer strategies, fine-tuning and curriculum learning, were utilized within the soft actor-critic architecture. Fine-tuning allows the agent to leverage pre-trained knowledge and adapt it to new tasks. Several …

abstract agent arm arxiv cs.ai cs.lg cs.ro curriculum curriculum learning efficiency knowledge manipulation movements reinforcement reinforcement learning robotic robotic arm robotic manipulation skills study train transfer type via