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cs.RO updates on arXiv.org

FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation DENALI: A Dataset Enabling Non-Line-of-Sight Spatial Reasoning with Low-Cost LiDARs SENSE: Stereo OpEN Vocabulary SEmantic Segmentation Continual Hand-Eye Calibration for Open-world Robotic Manipulation PLAF: Pixel-wise Language-Aligned Feature Extraction for Efficient 3D Scene Understanding GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow GIST: Multimodal Knowledge Extraction and Spatial Grounding via Intelligent Semantic Topology $π_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities R3D: Revisiting 3D Policy Learning Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios NEAT-NC: NEAT guided Navigation Cells for Robot Path Planning HRDexDB: A Large-Scale Dataset of Dexterous Human and Robotic Hand Grasps ADAPT: Benchmarking Commonsense Planning under Unspecified Affordance Constraints An Intelligent Robotic and Bio-Digestor Framework for Smart Waste Management Efficient closed-form approaches for pose estimation using Sylvester forms World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems A Nonasymptotic Theory of Gain-Dependent Error Dynamics in Behavior Cloning CooperDrive: Enhancing Driving Decisions Through Cooperative Perception SpaceMind: A Modular and Self-Evolving Embodied Vision-Language Agent Framework for Autonomous On-orbit Servicing HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning Failure Identification in Imitation Learning Via Statistical and Semantic Filtering A Dynamic-Growing Fuzzy-Neuro Controller, Application to a 3PSP Parallel Robot Vision-Language-Action Jump-Starting for Reinforcement Learning Robotic Agents A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization
Human vs. Teleoperated Robots in Vineyard Management: A S...
[Submitted on 5 Jul 2025 (v1), last revised 26 Aug 2026 (this ve · 2025-07-06 · via cs.RO updates on arXiv.org

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Abstract:Rising labor costs and narrow treatment windows have made teleoperated robots a proposed tool for vineyard scouting and treatment, but simulation-based comparisons of human and robotic performance are sensitive to modeling choices that can favor one agent before any trial runs: whether both can record a target's location, whether both are routed efficiently, and whether travel speeds are assessed consistently. This paper simulates a human operator against a teleoperated robot on two vineyard tasks, disease detection-and-treatment and yield-zone survey, holding both agents to matched location-marking and routing standards, using a routing strategy proven optimal for this topology, and modeling teleoperation-specific effects. Once information access and routing are held equal, task-time outcomes are governed largely by relative sustained travel speed: at the speeds modeled (1.4 m/s human, 0.9 m/s UGV), the human completes both tasks 43-48 percent faster, a gap persisting across a simulated eight-cycle season, while at speed parity the agents differ by only 9-12 percent, and every other parameter shifts the result by under 4 points. These results indicate the comparison is primarily a question of platform speed, and that the case for teleoperated robots should rest on labor availability, endurance, consistency, or hazard avoidance rather than completion time.

Submission history

From: Daniel Udekwe [view email]
[v1] Sat, 5 Jul 2025 21:36:02 UTC (2,991 KB)
[v2] Wed, 26 Aug 2026 14:43:12 UTC (889 KB)