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robotics

1,183 papers

Planning-aligned Token Compression for Long-Context Autonomous Driving

This work proposes COMPACT-VA, a planning-aligned working memory framework built on conditional VQ-VAE, compressing extended context into bounded representations, and evaluates on high-signal dynamic scenarios where historical context is most critical for behavior correctness, and accordingly design behavioral metrics.

Zhixuan Liang, Yuxiao Chen, Yurong You et al. · 1 citation
#artificial intelligence Preprint Aug 2026

ADEPT: Accelerating Dexterity via Pre-Training and Post-Training using Reinforcement Learning

We introduce Accelerating Dexterity via Pre-Training (ADEPT), a large-scale reinforcement learning (RL) framework for learning sim-to-real transferable dexterity across high degree-of-freedom (DoF) robot embodiments that can solve long-horizon tasks directly from raw visuo-tactile perception. ADEPT pretrains a dexterou...

Jayjun Lee, Jessica Yin, Asif Rana et al. · 2 citations
#artificial intelligence Preprint Aug 2026

DA-WAM: Decision-Aligned Future Latents for Driving World Models

DA-WAM is proposed, a framework that unifies predictive representation learning, action-conditioned future modeling, and trajectory scoring under a single decision-making objective and demonstrates state-of-the-art performance on NAVSIM-v1 and NAVSIM-v2.

Rui-Guo Zhong, Ben-Shan Ma, Xiao-Long Chen et al. · 4 citations
#artificial intelligence Preprint Aug 2026

Orienteering Problem with Uncertain Time-Varying Rewards: Framework and Benchmark for Everyday Service Robotics

We present the orienteering problem with uncertain time-varying rewards (OP-UTVR), a novel variant of the orienteering problem (OP). While most existing OP formulations assume rewards to be known in advance, practical applications involve uncertain and time-varying rewards, as with shifting customer demand for delivery...

Masafumi Endo, Kohei Honda, Yuu Jinnai et al. · 0 citations
#artificial intelligence Preprint Aug 2026

The Role of Grid Cells in Reducing Spatial Aliasing in Hippocampal Place Representations

Grid cell signals are introduced to mitigate spatial aliasing in geometrically ambiguous environments and indicate that grid cells provide information complementary to boundary-based inputs, yielding more reliable place representations in geometrically ambiguous environments.

Alexander B. Johnson, Obadah Ghizawi, A. Minai · 0 citations
#artificial intelligence Preprint Aug 2026

GigaBrain-WBC-0.5: A Behavior World Model for Robust Whole-Body Control with Environment Interaction

GigaBrain-WBC-0.5, the first Behavior World Model for humanoid whole-body control, is presented, which trains a causal Transformer to jointly predict its next action, next state, and the distribution over its next latent behavior command, so the network that acts also models how the environment shapes what it can do ne...

Zi-Yang Cheng, Tian-Shu Tang, Jin-Xi Lan et al. · 1 citation
#artificial intelligence Preprint Open access Aug 2026

A Metamorphic Artificial Age Score Decision-Support Prototype for Flight-Log-Based Drone Propeller Health Monitoring

Drone propeller faults can create safety and reliability risks when their effects are distributed across multiple flight-log channels rather than appearing as a single diagnostic signal. This paper proposes a Metamorphic Artificial Age Score (AAS) decision-support prototype for flight-log-based drone propeller health m...

Seyma Yaman Kayadibi · 0 citations

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Microsoft Research Blog Sep 23, 2026

Offloaded inference for real-world physical AI robotics

Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research.

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