FactoryNet is the first universal pretraining corpus for industrial time-series data with a shared S-E-F-C schema that supports cross-embodiment transfer and competitive anomaly detection.
Canonical reference
In: 2024 IEEE International Conference on Robotics and Automa- tion (ICRA)
Canonical reference. 76% of citing Pith papers cite this work as background.
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76% of classified citations
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extension 1
other 1
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representative citing papers
An asynchronous architecture decouples incremental voxel-based mapping from VLM-based semantic enrichment to produce queryable open-vocabulary 3D scene graphs that match or exceed prior methods on segmentation and grounding benchmarks.
MultiUAV-Plat supplies a new RESTful simulation platform and 1500-task benchmark where Agent4Drone reaches 57.9% task pass rate versus 30.6% for ReAct baseline across 75 multi-UAV missions.
Uni-Mo generates 7,488 language-annotated quadruped motions via LLM prompts and video diffusion, lifts them to 3D trajectories, and trains policies achieving 96.7% real-robot success on 392 sampled motions.
MPC-Injection biases off-policy RL locomotion policies toward controller-induced behavior basins by injecting MPC transitions into the replay buffer.
WireCraft is a new configurable simulation benchmark for industrial DLO manipulation with three task families, dual physics models, and shared evaluation of RL, IL, and VLA policies showing high success under privileged state but bottlenecks for vision-based methods.
FARM creates an open-vocabulary relational spatial memory that improves object retrieval recall by 164-224% over prior methods on 44k language queries across 67 scenes while running at 5-10 Hz.
SemanticXR introduces the first device-cloud system for real-time open-vocabulary semantic mapping and querying that organizes work around semantically identifiable objects to meet XR power, bandwidth, and memory limits.
CHORUS adapts a single VLA backbone for decentralized control of diverse robot teams, achieving 64-point gains over from-scratch decentralized baselines and outperforming centralized methods in real-world tasks using only local observations.
TIDES simulates realistic event camera streams in continuous time via dynamic Gaussian splatting with adaptive occlusion handling and sensor artifact modeling, claiming SOTA fidelity and better downstream transfer than prior methods.
Reinforcement learning policies for quadrotor inversion transitions with bidirectional thrust outperform optimization baselines by 32% in position RMSE and 57% in settling time in simulation, with successful hardware validation.
RS2AD-LiDAR reconstructs vehicle LiDAR data from roadside observations via coordinate transformation, virtual LiDAR modeling and resampling, claimed as the first such method, with experiments showing improved object detection when mixed with real data.
A smooth exponential obstacle cost with reduction factor in nonlinear MPC allows morphing quadrotors to traverse narrow gaps under limited 2D LiDAR perception.
A Galilean-equivariant filter jointly estimates INS navigation states and unknown GNSS time delays, preserving accuracy and consistency better than EKF in UAV flights and simulations with delays up to 500 ms.
Distance-r Independent Unlabeled Multi-Agent Pathfinding is PSPACE-complete, with reduction-based and configuration-generator algorithms that solve instances with hundreds of agents.
New framework for probabilistic safety shields in MDPs showing impossibility of strong classical guarantees and providing weaker but usable alternatives with offline and online constructions.
BehaviorBench reveals that self-play RL policies for autonomous driving overfit to their training traffic agents and do not generalize to other behaviors, motivating a hybrid rule-based plus learned planner.
An AI-agent social platform generated mostly neutral content whose use in fine-tuning reduced model truthfulness comparably to human Reddit data, suggesting limited unique harm but flagging tail risks like secret leaks.
LLM-Foraging uses off-the-shelf LLMs for decentralized tactical decisions in CPFA-based swarm foraging, collecting more resources than GA-tuned baselines across 36 varied configurations while showing greater consistency.
ESARBench is the first unified benchmark for MLLM-driven UAV agents that must explore, locate clues, and decide on victim positions in photorealistic simulated SAR environments.
The virtual object MPC framework enables stable shared teleoperation for transporting up to nine objects, cutting sliding distance by 72.45% and eliminating tip-overs compared to baseline.
ReV is a referring-aware visuomotor policy using coupled diffusion heads for real-time trajectory replanning in robotic manipulation, trained solely via targeted perturbations to expert demonstrations and achieving higher success rates in simulated and real tasks.
CROWD is a new global dataset of 51,753 continuous urban dashcam segments spanning over 20,000 hours from 238 countries, with manual labels and automated object detections for routine driving analysis.
AID trains diffusion policies via behavior cloning on existing MAIPP planners followed by RL fine-tuning to achieve faster execution and higher information gain in multi-agent coordination.
citing papers explorer
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Galilean State Estimation for Inertial Navigation Systems with Unknown Time Delay
A Galilean-equivariant filter jointly estimates INS navigation states and unknown GNSS time delays, preserving accuracy and consistency better than EKF in UAV flights and simulations with delays up to 500 ms.
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ESARBench: A Benchmark for Agentic UAV Embodied Search and Rescue
ESARBench is the first unified benchmark for MLLM-driven UAV agents that must explore, locate clues, and decide on victim positions in photorealistic simulated SAR environments.
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Towards Multi-Object Nonprehensile Transportation via Shared Teleoperation: A Framework Based on Virtual Object Model Predictive Control
The virtual object MPC framework enables stable shared teleoperation for transporting up to nine objects, cutting sliding distance by 72.45% and eliminating tip-overs compared to baseline.
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Sumo: Dynamic and Generalizable Whole-Body Loco-Manipulation
Test-time steering of pre-trained whole-body policies via sample-based planning lets legged robots generalize dynamic loco-manipulation to varied heavy objects and tasks without additional training or tuning.
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A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
The survey frames VLA models as pipelines that generate progressively grounded action tokens and classifies those tokens into eight types to guide future development.
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Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions
A survey of trajectory prediction techniques for autonomous vehicles that proposes a taxonomy, overviews the prediction pipeline, and highlights remaining research gaps.