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arXiv:2606. 08610v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a powerful paradigm for robot learning, particularly in sim-to-real settings, but its broader adoption remains limited by the engineering pipeline surrounding the algorithms.
arXiv:2609.16075v1 Announce Type: cross Abstract: Flexible robotic production requires joint decisions on process progression, material routing, resource assignment, temporary cooperation, and simult...
arXiv:2606. 31073v1 Announce Type: new Abstract: Large language models (LLMs) provide a promising interface for high-level robotic task planning, but their use in multi-UAV collaboration remains difficult to evaluate systematically.
arXiv:2606. 08729v1 Announce Type: cross Abstract: Simulation plays a key role in automated robotics research supported by large language models (LLMs).
arXiv:2607. 25728v1 Announce Type: cross Abstract: This paper presents a cooperative indoor UAV guidance framework that combines a shared voxel-map world model with a multi-agent Soft Actor-Critic (MASAC) controller.
arXiv:2606. 01478v1 Announce Type: cross Abstract: High-quality, large-scale synthetic data from simulations is becoming a cornerstone for pushing the capabilities of robot algorithms.