3 papers
cs.RO2025
Mind and Motion Aligned: A Joint Evaluation IsaacSim Benchmark for Task Planning and Low-Level Policies in Mobile Manipulation
Nikita Kachaev, Andrei Spiridonov, Andrey Gorodetsky +8
Benchmarks are crucial for evaluating progress in robotics and embodied AI. However, a significant gap exists between benchmarks designed for high-level language instruction follow…
cs.LG2025
M3PO: Massively Multi-Task Model-Based Policy Optimization
Aditya Narendra, Dmitry Makarov, Aleksandr Panov
We introduce Massively Multi-Task Model-Based Policy Optimization (M3PO), a scalable model-based reinforcement learning (MBRL) framework designed to address sample inefficiency in…
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…