cs.RO · 2026-07-30 · No. 69
Robotics, 2026-07-30.
5 new papers in cs.RO. Titles, authors,
abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →
01 — The papers
5 entries-
01
DLAM: Distributional Latent Actions with Temporal Constraints
Zuojin Tang, Feifan Luo, Haoyun Liu, Botai Yuan, Dekang Qi, Ronghan Chen, Yandan Yang, Tong Lin, Xinyuan Chang, Mu...
cs.RO · cs.AI · cs.CV
Vision-language-action (VLA) models remain constrained by scarce action-labeled robot data, whereas action-free videos offer abundant observations of physical change. Latent action models can extract such priors, but reconstruction-trained codes may predict future observations without the structure required for joint generation with robot actions. Existing structured methods add temporal constraints but retain deterministic transition points,...
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02
SymmGrid: Super-Scaling On-Robot Learning with Parallelized Symmetries and Egocentric-Exocentric Visual Perception
Gabe Everett, Brice Gunter, Ryan Vander Stelt, Cleiver Ruiz-Martinez, Blake Hull, Juan Rojas
cs.RO · cs.AI · cs.LG
Deep reinforcement policy learning directly in physical robots (on-robot learning) remains bottlenecked by slow wall-clock training times. We present SymmGrid, a trajectory level augmentation framework inspired by parallelized symmetries that super-scales group transformations to significantly accelerate on-robot learning in both egocentric and exocentric visual setups. We model a Markov Decision Process (MDP) under a symmetry tree, in which...
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03
BioVLN: A Simulation Platform for Visual Language Navigation in Biomedical Laboratories
Zhe Liu, Quan Lu, Zhaohui Du, Zhe Wang, Huanbo Jin, Jiaming Gu, Qi Wang, Ting Xiao, Minting Pan, Dongzhan Zhou
cs.RO · cs.AI
Biomedical laboratory robots must navigate to instruments before performing experimental procedures. Existing embodied navigation platforms are designed for household environments and treat a target as an object center or an arbitrary nearby position. This representation is inadequate for laboratory instruments, which must be approached from their operating side while maintaining safe clearance from surrounding equipment. We introduce BioVLN,...
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04
Reinforcement Learning on Cost-Constrained Quadrupedal Hardware
Javier C. Weddington, Bence P. Ölveczky, Stephen A. Baccus
cs.RO · cs.AI
Deploying learned control policies on low-cost robotic platforms introduces transport latencies and noisy motor feedback that systematically widens the sim-to-real gap. The chasm of simulation to deployment in hardware lies in the delay of the actuator reaching the commanded position. On platforms such as the Mini Pupper 2, a measured > $50 ms transport delay transforms the locomotion task from a standard Markov decision process into a...
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05
Self-Adaptive Learning and Model Predictive Control for Tracking Unknown Dynamics with No Regret
Atharva Navsalkar, Hongyu Zhou, Vasileios Tzoumas
cs.RO · cs.LG · eess.SY
We propose a self-adaptive online learning for control method for tracking unknown target dynamics. The target dynamics can exhibit switching behavior, particularly, a mixture of structured, random, and/or adversarial motion. Such challenging target tracking scenarios arise in applications of dynamic mapping, traffic control, and pursuit evasion, where robots need to track, pursue, or avoid collision with moving landmarks, objects, humans,...
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