Constrained Reinforcement Learning has recently gained increasing attention in the field of Safe Autonomous Driving, where the general mechanism is to maximize the expected reward while keeping the overall action risk bounded. In this way, the safety issues arising in AD can be mitigated through constrained actions. Ho...
Huan Rong, Chao Yin, Anouar Imel et al.· 0 citations
Adaptive Cruise Control (ACC) systems are typically calibrated for an average driver, often resulting in a mismatch between vehicle behavior and individual expectations during time-critical maneuvers such as highway overtaking. When the ACC is perceived as too conservative and inconsistent, drivers intervene through th...
Ruizheng Xu (Heudiasyc), Lounis Adouane (Heudiasyc), Javier Iba\~nez-Guzm\'an et al.· 0 citations
World-Action Models (WAMs) couple action generation with predictions of how physical interactions unfold. However, current post-deployment learning paradigms typically improve behavior without requiring better world predictions. Especially in dexterous manipulation, small execution errors can compound in high-dimension...
Xiang-Cheng Zhan, Zi-Rui Chen, Yi-Cheng Zhao et al.· 0 citations
A goal that is close in space can be far away in time. Obstacles, terrain, and the agent's own capabilities determine how long it takes to get there. Yet, critics in contrastive and survival reinforcement learning do not measure the distances in their representation space in units of time. We therefore introduce Chrono...
Nico Bohlinger, Jan Peters· 0 citations
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In urban low-altitude flight, buildings reshape ambient wind into spatially varying 3D flow, making unmanned aerial vehicle (UAV) energy depend on local wind exposure as well as path length. However, building-resolved wind information is rarely available when a mission must be planned. Computational fluid dynamics (CFD...
Shao-Xiang Qin, Yu-Cheng Zhao, Fuyuan Lyu et al.· 0 citations
SoRoMoX (Soft Robot Models in JAX), a fully numerical, JIT-compilable Python/JAX framework that runs directly on GPUs, is end-to-end differentiable with respect to states, inputs, and parameters, and is the first rod/strain-based soft-robot modeling framework that runs directly on GPUs.
Maximilian Stölzle, Solange Gribonval, D. Feliú-Talegon et al.· 1 citation
These results are a simulation-based control benchmark, not a clinical safety claim: the modeled tip is a rigid contact point, and flexible-thread mechanics, a validated force constraint, biological damage thresholds, and hardware-realistic sensing and timing remain necessary before deployment.
This paper instantiates the predictive interaction-dynamics framework of the base pHRI formulation on a SEA knee joint by implementing Bounded Assist-as-Needed scheduling, a corrective-channel energy tank, constrained OSQP stress cases, direct MuJoCo execution, and a posture-clamped MyoSuite knee slice.
MILE, a teleoperation-based data-collection system comprising the wearable MILE exoskeleton and the mechanically corresponding MILE-Tac robotic hand, and trained paired ACT and DP policies with and without tactile input on MILE-collected demonstrations for downstream imitation learning.
Jinda Du, Jie-Ji Ren, Qiao-Jun Yu et al.· 6 citations
We introduce CoinFT, a capacitive 6-axis force/torque (F/T) sensor that is compact, light, low-cost, and robust with an average root-mean-squared error of 0.16 N for force and 1.08 mN m for moment when the input ranges from 0-14 N and 0-5 N in normal and shear directions, respectively. CoinFT is a stack of two rigid PC...
Hojung Choi, Jun En Low, Tae Myung Huh et al.· 0 citations
The design, integration, and field deployment of an AI-assisted collaborative inspection cell at the Silverline kitchen-appliance factory is presented, developed within the AI-PRISM project.
Asya Ünal, Amr Okasha, Ege Çirakman et al.· 0 citations
WSM-Aware HRI is proposed, an IoT-enhanced modular framework that unifies diverse HRI breakdowns as World-State Mismatches (WSMs) between a human's instruction-implied assumptions and a robot's grounded world model built from multimodal perception and digital augmentation.
Han-Lin Zhang, Yu-Quan Wang, Tian-Wei Zhang et al.· 0 citations
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.
Gemini Robotics ER 2 helps robots reason, collaborate, and solve real-world tasks. It represents a step change in video understanding, tool orchestration, and multi-robot collaboration for robotic applications.
From feet to fingertips — we are teaching robots intelligent whole-body control, fine dexterity, and teamwork to complete a broad range of complex tasks.
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