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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
A Dual-Arm Robot that Manipulates Heavy Plates Cooperativ...
Shogo Hayakawa, Weiwei Wan, Keisuke Koyama, Kensuke Harada · 2022-03-20 · via cs.RO updates on arXiv.org

A vacuum lifter is widely used to hold and pick up large, heavy, and flat objects. Conventionally, when using a vacuum lifter, a human worker watches the state of a running vacuum lifter and adjusts the object's pose to maintain balance. In this work, we propose using a dual-arm robot to replace the human workers and develop planning and control methods for a dual-arm robot to raise a heavy plate with the help of a vacuum lifter. The methods help the robot determine its actions by considering the vacuum lifer's suction position and suction force limits. The essence of the methods is two-fold. First, we build a Manipulation State Graph (MSG) to store the weighted logical relations of various plate contact states and robot/vacuum lifter configurations, and search the graph to plan efficient and low-cost robot manipulation sequences. Second, we develop a velocity-based impedance controller to coordinate the robot and the vacuum lifter when lifting an object. With its help, a robot can follow the vacuum lifter's motion and realize compliant robot-vacuum lifter collaboration. The proposed planning and control methods are investigated using real-world experiments. The results show that a robot can effectively and flexibly work together with a vacuum lifter to manipulate large and heavy plate-like objects with the methods' support.