The trustworthy object detection capabilities of a novel Kolmogorov-Arnold network framework are examined here, and it offers a powerful tool for transparent and practical perception component for autonomous and multimodal artificial intelligence applications.
Marios Impraimakis, Daniel Vazquez, Fei Zhou· Scientific Reports· 0 citations
Visuomotor imitation policies can achieve high performance under in-distribution visual conditions yet fail when visually similar objects or receptacles are introduced. We study this behavior as a problem of conditional visual grounding: the visual target required for successful control changes with the manipulation ph...
Vivek Chavan, Peng-Tao Xie, Ya-Huan Shi et al.· 0 citations
A large-scale robotic manipulation dataset and benchmark for diagnosing embodied reasoning in VLA models, and establishes RoboSPA as a challenging diagnostic benchmark for developing more capable, reliable, and generalizable embodied agents.
Zhen-Xuan Fan, Bo Zhang, Yu-Tong Lin et al.· 0 citations
This paper addresses navigation by composite heterogeneous robots in a decentralized system when policy reasoning and local control operate at different update levels when policy reasoning and local control operate at different update levels using a NetLogo--Python implementation.
Chong-Wen Dong, Mithun Paul Saint-Germain, Pinjari Asif et al.· 0 citations
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It is demonstrated that a single learned traffic prior can simultaneously improve motion planning and provide a realistic framework for systematic planner robustness evaluation.
Arka Pal, Rajesh Kumar, Hannes Eriksson et al.· 0 citations
This paper presents the first attempt to estimate multi-person 3D poses solely from acoustic signals, a novel encoder-decoder framework consisting of two key components that precisely reconstructs frame-wise individual poses.
Yusuke Oumi, Yuto Shibata, Go Irie et al.· 0 citations
A dual-part MLBNet architecture is designed with multi-lateral encoder blocks and multi-head decoder branches for class-aware segmentation in cardiovascular catheterization scenes, which showed the dual-part models could effectively separate guidewire, catheter, vessels and background pixels to their classes of members...
O. Omisore, A. Elazab, Ali Shahidinejad et al.· 0 citations
Unattended interactive autonomy - machines that step into danger in place of humans and complete tasks with human tools - remains a missing capability in mission-critical operations. These domains offer scarce training data and only onboard compute, yet deployed systems must face novelty without erasing prior competenc...
Amarjot Singh, Tanmay R. Pancholi, Jainam Kothari et al.· 0 citations
Across DINOv2-giant and MetaCLIP-H with real-background queries, the largest fused-accuracy advantage of the real prototypes over either control is one percentage point; larger differences favor controls, by up to 2.8 points in arm means.
VLA-Precision, an efficient real-world online RL framework featuring the Asymmetric Co-Bootstrapping (ACoB) algorithm and the ACoB-Stream architecture, and ACoB-Stream, a closed-loop experience--policy architecture that establishes invariant-state decoupling and on-demand streaming as design principles, deliver up to 1...
Chen-Yu Su, Zhao-Long Shen, Yuan Qian et al.· 0 citations
World action models (WAMs) condition robot actions on predicted futures, but iterative video rollout increases deployment latency. We ask whether action generation requires the evolving rollout trajectory or only its future representation. Across four WAMs on 40 simulated robotic manipulation tasks, paired closed-loop...
Chu-Shan Zhang, Jin-Guang Tong, Xue-Song Li et al.· 3 citations
This work introduces RedFlow, an offline post-training method for flow-matching VLA policies that requires neither external HIL corrections nor online data collection during post-training, and improves average success across four LIBERO suites.
A new system identifies and corrects unreliable object descriptions stored in a robot’s memory, improving the robot’s ability to interact with its environment.
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.
