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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 Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment RobotPan: A 360$^\circ$ Surround-View Robotic Vision System for Embodied Perception Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics GeoVision-Enabled Digital Twin for Hybrid Autonomous-Teleoperated Medical Responses 4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Multi-modal panoramic 3D outdoor datasets for place categorization Learning Probabilistic Responsibility Allocations for Multi-Agent Interactions Solving Physics Olympiad via Reinforcement Learning on Physics Simulators StarVLA-$α$: Reducing Complexity in Vision-Language-Action Systems Grounded World Model for Semantically Generalizable Planning SCORP: Scene-Consistent Multi-agent Diffusion Planning with Stable Online Reinforcement Post-Training for Cooperative Driving Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical Systems AffordSim: A Scalable Data Generator and Benchmark for Affordance-Aware Robotic Manipulation Efficient Emotion-Aware Iconic Gesture Prediction for Robot Co-Speech Minimal Embodiment Enables Efficient Learning of Number Concepts in Robot Learning to Forget -- Hierarchical Episodic Memory for Lifelong Robot Deployment 3D-Anchored Lookahead Planning for Persistent Robotic Scene Memory via World-Model-Based MCTS EmbodiedGovBench: A Benchmark for Governance, Recovery, and Upgrade Safety in Embodied Agent Systems Federated Single-Agent Robotics: Multi-Robot Coordination Without Intra-Robot Multi-Agent Fragmentation Robust Adversarial Policy Optimization Under Dynamics Uncertainty BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence Genie 4D: Semantic-Prior-Guided 4D Dynamic Scene Reconstruction RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models PhysInOne: Visual Physics Learning and Reasoning in One Suite C$^2$T: Captioning-Structure and LLM-Aligned Common-Sense Reward Learning for Traffic--Vehicle Coordination WOMBET: World Model-Based Experience Transfer for Robust and Sample-efficient Reinforcement Learning Accelerating Transformer-Based Monocular SLAM via Geometric Utility Scoring 3D-VCD: Hallucination Mitigation in 3D-LLM Embodied Agents through Visual Contrastive Decoding Action Images: End-to-End Policy Learning via Multiview Video Generation Towards Generalizable Robotic Manipulation in Dynamic Environments General-purpose LLMs as Models of Human Driver Behavior: The Case of Simplified Merging Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters IROSA: Interactive Robot Skill Adaptation using Natural Language Online Navigation Planning for Long-term Autonomous Operation of Underwater Gliders Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation From Instruction to Event: Sound-Triggered Mobile Manipulation Self-Organizing Dual-Buffer Adaptive Clustering Experience Replay (SODACER) for Safe Reinforcement Learning in Optimal Control Enhanced-FQL($λ$), an Efficient and Interpretable RL with novel Fuzzy Eligibility Traces and Segmented Experience Replay LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving Learning to Plan, Planning to Learn: Adaptive Hierarchical RL-MPC for Sample-Efficient Decision Making Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets? Robust Verification of Controllers under State Uncertainty via Hamilton-Jacobi Reachability Analysis Towards Deploying VLA without Fine-Tuning: Plug-and-Play Inference-Time VLA Policy Steering via Embodied Evolutionary Diffusion Volumetric Ergodic Control RoboTAG: End-to-end Robot Configuration Estimation via Topological Alignment Graph TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research Multimodal Diffusion Forcing for Forceful Manipulation X-Diffusion: Training Diffusion Policies on Cross-Embodiment Human Demonstrations Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data AFFORD2ACT: Affordance-Guided Automatic Keypoint Selection for Generalizable and Lightweight Robotic Manipulation HAMLET: Switch your Vision-Language-Action Model into a History-Aware Policy TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance Multi-Modal Manipulation via Multi-Modal Policy Consensus AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving Constrained Decoding for Safe Robot Navigation Foundation Models FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving LLM-based Realistic Safety-Critical Driving Video Generation Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents Learning to Play Piano in the Real World Scalable Unseen Objects 6-DoF Absolute Pose Estimation with Robotic Integration Sixth-Sense: Self-Supervised Learning of Spatial Awareness of Humans from a Planar Lidar Curriculum-based Sample Efficient Reinforcement Learning for Robust Stabilization of a Quadrotor Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI Convex Hulls of Reachable Sets
Efficient Autonomous Navigation for Terrestrial Insect-Machine Hybrid Systems
Huu Duoc Nguyen, Van Than Dung, Hirotaka Sato, T. Thang Vo-Doan · 2022-04-28 · via cs.RO updates on arXiv.org

While bio-inspired and biomimetic systems draw inspiration from living materials, biohybrid systems incorporate them with synthetic devices, allowing the exploitation of both organic and artificial advantages inside a single entity. In the challenging development of centimeter-scaled mobile robots serving unstructured territory navigations, biohybrid systems appear as a potential solution in the forms of terrestrial insect-machine hybrid systems, which are the fusion of living ambulatory insects and miniature electronic devices. Although their maneuver can be deliberately controlled via artificial electrical stimulation, these hybrid systems still inherit the insects' outstanding locomotory skills, orchestrated by a sophisticated central nervous system and various sensory organs, favoring their maneuvers in complex terrains. However, efficient autonomous navigation of these hybrid systems is challenging. The struggle to optimize the stimulation parameters for individual insects limits the reliability and accuracy of navigation control. This study overcomes this problem by implementing a feedback control system with an insight view of tunable navigation control for an insect-machine hybrid system based on a living darkling beetle. Via a thrust controller for acceleration and a proportional controller for turning, the system regulates the stimulation parameters based on the instantaneous status of the hybrid robot. While the system can provide an overall success rate of ~71% for path-following navigations, fine-tuning its control parameters could further improve the outcome's reliability and precision to up to ~94% success rate and ~1/2 body length accuracy, respectively. Such tunable performance of the feedback control system provides flexibility to navigation applications of insect-machine hybrid systems.