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cs.RO2026
Knowledge-Guided Manipulation Using Multi-Task Reinforcement Learning
Aditya Narendra, Mukhammadrizo Maribjonov, Dmitry Makarov +2
This paper introduces Knowledge Graph based Massively Multi-task Model-based Policy Optimization (KG-M3PO), a framework for multi-task robotic manipulation in partially observable…
cs.RO2025
SGN-CIRL: Scene Graph-based Navigation with Curriculum, Imitation, and Reinforcement Learning
Nikita Oskolkov, Huzhenyu Zhang, Dmitry Makarov +2
The 3D scene graph models spatial relationships between objects, enabling the agent to efficiently navigate in a partially observable environment and predict the location of the ta…
cs.RO2025
TOCALib: Optimal control library with interpolation for bimanual manipulation and obstacles avoidance
Yulia Danik, Dmitry Makarov, Aleksandra Arkhipova +2
The paper presents a new approach for constructing a library of optimal trajectories for two robotic manipulators, Two-Arm Optimal Control and Avoidance Library (TOCALib). The opti…