arXiv:2603.24241v1 Announce Type: cross
Abstract: Safe navigation in complex environments remains a central challenge for reinforcement learning (RL) in robotics. This paper introduces Continuous Space-Time Empowerment for Physics-informed (C-STEP) sa…
arXiv:2603.24324v1 Announce Type: new
Abstract: Designing effective auxiliary rewards for cooperative multi-agent systems remains a precarious task; misaligned incentives risk inducing suboptimal coordination, especially where sparse task feedback fai…
arXiv:2603.24475v1 Announce Type: new
Abstract: Accurate forecasting of state-of-health (SOH) is essential for ensuring safe and reliable operation of lithium-ion cells. However, existing models calibrated on laboratory tests at specific conditions of…
arXiv:2603.24503v1 Announce Type: new
Abstract: The practical deployment of nonlinear model predictive control (NMPC) is often limited by online computation: solving a nonlinear program at high control rates can be expensive on embedded hardware, espe…
arXiv:2602.21415v3 Announce Type: replace
Abstract: Selecting the right deep learning model for power grid forecasting is challenging, as performance heavily depends on the data available to the operator. This paper presents a comprehensive benchmark …
arXiv:2603.18853v2 Announce Type: replace-cross
Abstract: Autonomous aerial vehicles (AAVs) empower sixth-generation (6G) Internet-of-Things (IoT) networks through mobility-driven data collection. However, conventional reward-driven reinforcement lear…
arXiv:2603.23777v1 Announce Type: cross
Abstract: During human motor skill training and physical rehabilitation, there is an inherent trade-off between task difficulty and user performance. Characterizing this trade-off is crucial for evaluating user …
arXiv:2603.23983v1 Announce Type: cross
Abstract: Recent advances in real-time interactive text-driven motion generation have enabled humanoids to perform diverse behaviors. However, kinematics-only generators often exhibit physical hallucinations, pr…
arXiv:2603.20131v2 Announce Type: replace-cross
Abstract: Getting a real cybersecurity risk assessment for a small organization is expensive — a NIST CSF-aligned engagement runs $15,000 on the low end, takes weeks, and depends on practitioners who ar…
arXiv:2603.24130v1 Announce Type: new
Abstract: This paper presents an equivariant filter (EqF) transformation approach for visual–inertial navigation. By establishing analytical links between EqFs with different symmetries, the proposed approach ena…