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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
"Connected Researches" in "Smart Lab Bubble": A Lifeline ...
Prabath Chaminda Abeysiriwardana, Udith K. Jayasinghe-Mudalige, · 2021-04-29 · via cs.RO updates on arXiv.org

Research in commercial agriculture is the best strategy that can be adopted by a country to keep on track of the second sustainable goal -- zero hunger by 2030. Analyzing the drawbacks of present research environment and find solutions through digital intervention would be ideal solution to de-isolate the research out come in light of disruptions caused by the Covid pandemic. The performance of the research institutes is not expected to remain the same and would prefer to be stagnated at a lower level. The right evacuation plan that could be worked out by establishing connected research through the digital solution and followed by digitally endorsed performance monitoring and evaluation would be saviour for keeping the research in commercial agriculture live at this pandemic. This paper will discuss what are the problems in carrying out research in commercial agriculture and propose a conceptual model to connect research beyond physical presence by digital transformations in organization design of research institutes in light of Covid-19. Further, digitally endorsed performance measurements and evaluation is envisaged in a digitally empowered connected lab complex -- "Smart Lab Bubble" that is further facilitated through policy measures. The connected lab complex called the "Smart Lab Bubble" concept we present here could be viewed or applied in different perspectives to engineer the real need of the time for the sustainability of research in commercial agriculture. Further, it could be adopted in research in other life science areas.