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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 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FORTE: Tactile Force and Slip Sensing on Compliant Fingers for Delicate Manipulation
Siqi Shang, Mingyo Seo, Yuke Zhu, Lillian Chin · 2025-06-24 · via cs.RO updates on arXiv.org

Handling fragile objects remains a major challenge for robotic manipulation. Tactile sensing and soft robotics can improve delicate object handling, but typically involve high integration complexity or slow response times. We address these issues through FORTE, an easy-to-fabricate tactile sensing system. FORTE uses 3D-printed fin-ray grippers with internal air channels to provide low-latency force and slip feedback. This feedback allows us to apply just enough force to grasp objects without damaging them. We accurately estimate grasping forces from 0-8 N with an average error of 0.2 N, and detect slip events within 100 ms of occurring. FORTE can grasp a wide range of slippery, fragile, and deformable objects, including raspberries and potato chips with 92% success and achieves 93% accuracy in detecting slip events. These results highlight FORTE's potential as a robust solution for delicate robotic manipulation. Project page: https://merge-lab.github.io/FORTE/

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