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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
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…