This paper presents a framework that enables multi-agent systems to learn controllers independently through integral reinforcement learning while guaranteeing modular stability when connected. The framework addresses a gap: existing modular control methods require analytical models and cannot handle learned controllers...
Jie Ren, Bahram Shafai· International journal of res...· 0 citations
How can robot policies learn more effectively from a fixed demonstration budget? The first Real-world Embodied AI Learning (REAL-I) Challenge at ICRA 2026 examined this question through simulation, real-robot evaluation, and an on-site final on a shared dual-arm humanoid platform. We describe the challenge tasks, data...
Jia-Ming Wang, Ji-Zhuo Chen, Di-Wen Liu et al.· 0 citations
TS-Mask VLA is built upon two key designs: a Discrete Diffusion Action Expert equipped with a Bridge Attention conditioning bridge, which enables multi-layer conditioning from the VLM and facilitates more accurate and stable action generation; and a temporal-spatial 2D masking strategy for discrete action tokens that s...
Integral reinforcement learning (IRL) solves the linear quadratic regulator (LQR) problem without requiring the system dynamics matrix, but needs full state measurements. In the absence of states, a dedicated PI observer structure can be used in the learning process, which avoids the limitation of P observer. This pape...
Jie Ren, Bahram Shafai· International Conference on...· 0 citations
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