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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
Improving Swimming Performance in Soft Robotic Fish with ...
Kevin Soto, Isabel Hess, Brandon Schrader, Shan He, Patrick Musg · 2025-04-16 · via cs.RO updates on arXiv.org

Bio-inspired underwater vehicles could yield improved efficiency, maneuverability, and environmental compatibility over conventional propeller-driven underwater vehicles. However, to realize the swimming performance of biology, there is a need for soft robotic swimmers with both distributed muscles and kinematic feedback. This study presents the design and swimming performance of a soft robotic fish with independently controllable muscles and embedded kinematic sensing distributed along the body. The soft swimming robot consists of an interior flexible spine, three axially distributed sets of HASEL artificial muscles, embedded strain gauges, a streamlined silicone body, and off-board electronics. In a fixed configuration, the soft robot generates a maximum thrust of 7.9 mN when excited near its first resonant frequency (2 Hz) with synchronized antagonistic actuation of all muscles. When excited near its second resonant frequency (8 Hz), synchronized muscle actuation generates 5.0 mN of thrust. By introducing a sequential phase offset into the muscle actuation, the thrust at the second resonant frequency increases to 7.2 mN, a 44% increase from simple antagonistic activation. The sequential muscle activation improves the thrust by increasing 1) the tail-beat velocity and 2) traveling wave content in the swimming kinematics by four times. Further, the second resonant frequency (8 Hz) generates nearly as much thrust as the first resonance (2 Hz) while requiring only $\approx25$% of the tail displacement, indicating that higher resonant frequencies have benefits for swimming in confined environments where a smaller kinematic envelope is necessary. These results demonstrate the performance benefits of independently controllable muscles and distributed kinematic sensing, and this type of soft robotic swimmer provides a platform to address the open challenge of sensorimotor control.