cs.RO · 2026-06-18 · No. 27

Robotics, 2026-06-18.

7 new papers in cs.RO. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

7 entries
  1. 01

    Learning to Annotate Delayed and False AEB Events: A Practical System for Extreme Class Imbalance and Asymmetric Label Noise

    Mengxiang Hao, Xin Jiang, Xinghao Huang, Wenliang Su, Zhiteng Wang, Junjie Rao, Xiaotian Yang, Wei Liao, Chengyu...

    cs.RO · cs.LG

    Autonomous Emergency Braking (AEB) optimization relies on accurately annotated real-world trigger events, particularly rare but critical delayed and false AEB triggers that expose system deficiencies. However, these minority samples comprise less than 5% of thousands of daily triggers, making manual annotation prohibitively expensive at scale. We present the first automated AEB annotation framework to address this problem. During development,...

    arxiv.org/abs/2606.19186 · PDF

  2. 02

    Hardware- and Vision-in-the-Loop Validation of Deep Monocular Pose Estimation for Autonomous Maritime UAV Flight

    Maneesha Wickramasuriya, Beomyeol Yu, Jaden Shin, Mason Huslig, Taeyoung Lee, Murray Snyder

    cs.RO · cs.AI · eess.SY

    Autonomous UAV operations on ships require reliable vision-based relative pose estimation, yet at-sea validation is costly, weather-dependent, and risky. This paper presents a hardware-validated vision-in-the-loop framework that enables fully autonomous indoor flight while emulating photorealistic maritime environments. Rendered maritime views are processed onboard by a deep transformer-based monocular pose estimator. Delayed vision...

    arxiv.org/abs/2606.19176 · PDF

  3. 03

    Space Is Intelligence: Neural Semigroup Superposition for Riemannian Metric Generation

    Chenghao Xu

    cs.RO · cs.AI

    Traditional approaches place intelligence in the agent, whether as a learned policy or a search procedure. We instead place intelligence in the space itself: a scene induces a Riemannian metric on the configuration manifold, and action reduces to following the geodesics of that metric rather than invoking a separate planner or collision checker. A single Encoder-Router network realizes this idea through three complementary parameter groups --...

    arxiv.org/abs/2606.18828 · PDF

  4. 04

    Generating Natural and Expressive Robot Gestures through Iterative Reinforcement Learning with Human Feedback using LLMs

    Chris Lee, Flora Salim, Benjamin Tag, Francisco Cruz

    cs.RO · cs.AI

    Expressive gestures are essential for natural and effective communication, complementing speech when verbal cues alone are insufficient (e.g., pointing). For social robots such as the humanoid Pepper, producing natural and expressive movements is critical for improving human-robot interaction (HRI) and long-term acceptance. However, generating gestures remains challenging due to reliance on expert-authored animations, resulting in rigid...

    arxiv.org/abs/2606.18747 · PDF

  5. 05

    Two-Phase Bilevel Search for the Moving-Target Traveling Salesman Problem with Moving Obstacles

    Allen George Philip, Anoop Bhat, Sivakumar Rathinam, Howie Choset

    cs.RO · cs.AI · math.CO · math.OC

    The Moving-Target Traveling Salesman Problem (MT-TSP) seeks a minimum cost trajectory for an agent that departs from a static depot, visits a set of moving targets, each within one of their assigned time windows, and returns to the depot. In this article, we study the Moving-Target Traveling Salesman Problem with Moving Obstacles (MT-TSP-MO), a generalization of the MT-TSP where the agent trajectory must avoid moving obstacles. We present a...

    arxiv.org/abs/2606.18730 · PDF

  6. 06

    Leveraging Energy Features for Surface Classification with Deep Learning: A Comparative Analysis Across Three Independent Datasets

    Alexander Belyaev, Oleg Kushnarev

    cs.RO · cs.AI · cs.LG

    The energy-based method remains a comparatively underexamined approach for surface classification in mobile robotics, despite promising results in constrained environments. This study evaluated the viability of using energy-derived features as either a standalone classification modality or as supplementary input to inertial data. A comprehensive evaluation was conducted across three publicly available datasets, comparing the performance of...

    arxiv.org/abs/2606.18698 · PDF

  7. 07

    EffiNav: Fusing Depth and Vision-Language for Efficient Object Goal Navigation

    Zecheng Yin, Benedict Jun Ma

    cs.RO · cs.AI

    To locate a target object while exploring the unknown environment is a fundamental capability for autonomous agents, with applications ranging from search-and-rescue to field robots. A simplified version of such task is Object Goal Navigation (ObjNav). In ObjNav, successful arrival at the target object provides a basic measure of performance; however, the efficiency of the navigation trajectory is equally important, as it indicates how...

    arxiv.org/abs/2606.18634 · PDF

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