cs.RO · 2026-07-15 · No. 54
Robotics, 2026-07-15.
10 new papers in cs.RO. Titles, authors,
abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →
01 — The papers
10 entries-
01
UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies
Lirui Zhao, Modi Shi, Li Chen, Qi Liu, Ping Luo, Hongyang Li
cs.RO · cs.AI
Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the quality of these signals critical. Since such dense labels are rarely available at scale, normalized time within a demonstration is often used as a scalable substitute: later frames are treated as higher progress. However, this time-derived label is only a noisy proxy...
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02
Unveiling Complex Collective Behaviors from Simple Rewards
Yize Mi, Jianan Li, Liang Li, Shiyu Zhao
cs.RO · cs.AI · eess.SY
Multi-agent Reinforcement Learning (MARL) holds great potential for robot swarms, but the black-box nature of neural policies complicates strategic analysis, limiting multi-robot applications. Furthermore, complex swarm behaviors can surprisingly emerge from simple rewards without explicit aggregation incentives. Unveiling the mechanisms behind this emergence is critical, but the disconnection between simple rewards and collective behaviors...
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03
PixelLoop: Shortcut Topological Navigation with Pixel-Level Loops
Sarthak Chittawar, Vansh Garg, Aditya Vadali, Krish Pandya, Rohit Jayanti, Sourav Garg, Madhava Krishna
cs.RO · cs.AI
Although topological mapping and navigation have been studied extensively, the specific role and downstream effect of loop closures in purely topological representations has received relatively little attention. Importantly, loop closure over topological maps is distinct from loop closure over globally referenced trajectories and metric maps. Building on recent denser topologies grounded in pixel-level, relative 3D geometry, we propose...
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04
Autonomous Tracking and Terminal Guidance of Moving Targets for Fixed-Wing UAVs
Wei-Hao Liou, Teng-Hu Cheng
cs.RO · cs.AI · eess.SY
This study introduces a unified control framework for fixed-wing unmanned aerial vehicles (UAVs) fitted with a pan-tilt (PT) camera, intended to perform an end-to-end mission spanning from initial target detection to accurate terminal engagement. The proposed system employs a three-phase strategy: a vision-based target acquisition phase, an NMPC-based tracking phase, and a terminal guidance phase. During tracking, the framework uses an...
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05
Directional Constraints for Efficient Exploration in Safe Reinforcement Learning
Paolo Magliano, Puze Liu, Jan Peters, Davide Tateo, Raffaello Camoriano
cs.RO · cs.LG
Reinforcement Learning has revolutionized the landscape of robotic research, allowing robust learning of complex robotic skills in simulation. However, real-world deployment in open-ended environments requires strong safety guarantees to prevent dangerous or harmful behaviors. Safe Reinforcement Learning methods address this requirement by enforcing safety constraints. Nevertheless, learning under constraints often reduces learning speed and...
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06
Jetson-PI: Towards Onboard Real-Time Robot Control via Foresight-Aligned Asynchronous Inference
Zebin Yang, Qi Wang, Yunhe Wang, Xiurui Guo, Bo Yu, Shaoshan Liu, Jiafeng Xu, Hao Dong, Meng Li
cs.RO · cs.AI
Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard devices, such as the Jetson Orin, remains challenging due to their high computational complexity, which leads to substantial inference latency and low control frequency. Asynchronous inference can partially mask this latency by parallelizing action execution and subsequent inference, but it...
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07
Mind the Gap: Promises and Pitfalls of Hierarchical Planning in LeWorldModel
Niccolò Caselli, Salvatore Lo Sardo, Francesco Massafra, Ippokratis Pantelidis, Samuele Punzo, Sathya Kamesh Bhethanabhotla
cs.RO · cs.AI · cs.LG
We investigate whether temporal hierarchy can improve LeWorldModel on long-horizon goal-conditioned control. We introduce Hi-LeWM, an extension that freezes the pretrained low-level LeWM and adds high-level planning over latent subgoals. We evaluate Hi-LeWM on PushT and Cube across increasing goal offsets. Hierarchy does not automatically improve performance: at short horizons, the best configuration uses a one-step high-level horizon, while...
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08
GaitSpan: Growing Humanoid Locomotion from Walking to Running
Kwan-Yee Lin, Zilin Wang, Janelle J. Liu, Stella X. Yu
cs.RO · cs.AI · cs.CV
A humanoid that can walk should not relearn locomotion from scratch to jog or run. Yet current approaches often obtain gait diversity by prescribing gait schedules, imitating motion clips, training experts to switch between or distilling skills into one policy. These strategies can produce impressive behaviors, but offer limited flexibility across continuous speed commands, terrains, and morphologies. We study skill growth with GaitSpan, a...
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09
Robust In-Hand Manipulation via Priors in Reinforcement Learning and Mechanical Design
Yifei Chen, Shihan Lu, Ed Colgate, Kevin Lynch
cs.RO · cs.LG
In-hand manipulation without external sensing is challenging due to uncertainties from finger-object contacts and disturbances by gravity. While reinforcement learning has shown promise in learning complex finger gaiting, existing approaches do not prioritize maintaining well-conditioned grasps for sustained manipulation. We introduce two complementary physics priors for robust in-hand rolling: a global grasp-quality prior derived from...
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10
Enabling 24-hour Agricultural Robotics: Unsupervised Day-to-Night Cross-Modal Image Translation for Nighttime Visual Navigation
Robel Mamo, Rajitha de Silva, Grzegorz Cielniak, Taeyeong Choi
cs.RO · cs.AI · cs.CV
While visual navigation has been extensively studied in agricultural robotics, most existing systems assume daytime conditions. In fact, deploying autonomous robots at night offers significant advantages, including 24-hour crop and soil monitoring, fruit harvesting, and nocturnal pest detection. Modern vision-based systems, however, rely heavily on large-scale well-annotated image datasets, which remains challenging to obtain for nighttime...
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