Robot Localization Systems
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Related Articles from SNS
Adversarial Attacks on Robot Localization Systems via Deep Feature Perturbation
arXiv:2606.01892v1 Announce Type: new Abstract: Robot localization systems are critical for autonomous navigation and safety. Adversarial perturbations can mislead these systems, resulting in mislocalization, navigation errors, or unsafe interactions, especially in mission-critical scenarios. This paper investigates the vulnerability of deep learning based localization pipelines to adversarial attacks.
A Kinetic Theory of Encounter-Based Information Propagation in Multi-Robot Systems
arXiv:2606.02296v1 Announce Type: new Abstract: Multi-robot systems cannot assume persistent network connectivity. We study this problem through target tracking, where performance depends on how quickly target information is sensed, transported through the team, and used before it becomes stale. When robots exchange information only through physical encounters, tracking becomes a kinetic information-transport problem: robot motion induces encounters, encounters carry target-state estimates,...
Dynamic Multi-Agent Pickup and Delivery in Robotic Cellular Warehousing Systems
arXiv:2606.05669v1 Announce Type: new Abstract: Robotic Cellular Warehousing Systems (RCWS) give rise to multi-agent pickup and delivery (MAPD) processes in which robots sequentially collect multiple stock-keeping units (SKUs) for each order. Unlike classical MAPD formulations that assume static tasks, real warehouse operations often involve dynamic order evolution, where new SKUs may be appended to an order while it is being executed. Motivated by this practical requirement, this letter...
3D RL-DWA: A Hybrid Reinforcement Learning and Dynamic Window Approach for Goal-Directed Local Navigation in Multi-DoF Robots
Announce Type: replace Abstract: In this paper, we present a novel hybrid approach that combines Reinforcement Learning (RL) with Dynamic Window Approach (DWA) for adaptive 3D local navigation of high-degree-of-freedom robotic systems. Our method leverages sparse point cloud data to dynamically adjust both the motion and the shape of a deformable microrobot, enabling the system to navigate toward a goal in complex, constrained environments while maximizing the occupied volume. We evaluate...
Autonomous Navigation System for Library Service Robot Based on Unitree Go2 Edu
arXiv:2606.03340v1 Announce Type: new Abstract: Libraries require autonomous robots to move quietly through narrow aisles while remaining safe around readers, chairs, bags, and carts. This paper presents a ROS 2 navigation system for a Unitree Go2 Edu quadruped equipped with a 4D LiDAR, a front depth camera, and an IMU. Rather than assuming the library is rough terrain, we target the practical mobility discontinuities of real deployments, including floor transitions, temporary clutter, and...
A Conversational Framework for Human-Robot Collaborative Manipulation with Distributed Generative AI models
arXiv:2606.06061v1 Announce Type: new Abstract: This paper presents a distributed conversational framework for human-robot collaborative manipulation that integrates local language and vision-language models (VLMs) with a Robot Operating System 2 (ROS 2)-based execution stack. Language understanding, visual grounding, orchestration, and motion execution run as separate ROS 2 nodes, enabling flexible deployment across distributed hardware while maintaining a responsive control loop. From...
Efficient Minimal Solvers for Relative Pose Estimation in Autonomous Driving Applications
arXiv:2606.09569v1 Announce Type: new Abstract: With the advancement of visual sensing systems, computer vision is playing an increasingly important role in autonomous driving and robot navigation. Relative pose estimation in multi-camera systems is essential for accurate vehicle localization and environment perception, demanding high real-time performance and robustness. Existing methods, however, often involve high computational costs and rely heavily on abundant feature matches, limiting...
Safe and Energy-Aware Multi-Robot Density Control via PDE-Constrained Optimization for Long-Duration Autonomy
arXiv:2604.15524v3 Announce Type: replace Abstract: This paper presents a novel density control framework for multi-robot systems with spatial safety and energy sustainability guarantees. Stochastic robot motion is encoded through the Fokker-Planck Partial Differential Equation (PDE) at the density level. Control Lyapunov and control barrier functions are integrated with PDEs to enforce target density tracking, obstacle region avoidance, and energy sufficiency over multiple charging cycles.
Multi-Robot Bearing-only Pose Estimation via Angle Rigidity
arXiv:2606.03931v1 Announce Type: new Abstract: This letter proposes a novel distributed bearing-based pose estimator for time-varying multi-robot systems. The method uses angles computed from body-frame bearings to estimate the robots' positions in $\mathbb{R}^3$ without knowledge of their orientations. The orientations in $\mathrm{SO}(3)$ are recovered from the estimated positions, the bearings, and the bearing derivatives.
SPIRONet: Spatial-Frequency Learning and Graph-based Channel Interaction Network for Vessel Segmentation
Announce Type: replace-cross Abstract: Automatic vessel segmentation plays a pivotal role in the development of next-generation interventional navigation systems for surgical robotics. However, current approaches still suffer from suboptimal segmentation performance under challenging intraoperative conditions, such as low-signal-to-noise ratio (SNR), small or slender vessels, and strong interference. In this study, a novel spatial-frequency learning and graph-based channel interaction...