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cs.RO2026

Learning to Localize Reference Trajectories in Image-Space for Visual Navigation

Finn Lukas Busch, Matti Vahs, Quantao Yang +4

We present LoTIS, a model for visual navigation that provides robot-agnostic image-space guidance by localizing a reference RGB trajectory in the robot's current view, without requ…

cs.RO2026

Learned Controllers for Agile Quadrotors in Pursuit-Evasion Games

Alejandro Sanchez Roncero, Yixi Cai, Olov Andersson +1

In this letter we study 1v1 quadrotor pursuit-evasion, where a pursuer and an evader are trained via reinforcement learning (RL) by competing against each other. Such adversarial s…

cs.RO2026

DIV-Nav: Open-Vocabulary Spatial Relationships for Multi-Object Navigation

Jesús Ortega-Peimbert, Finn Lukas Busch, Timon Homberger +2

Advances in open-vocabulary semantic mapping and object navigation have enabled robots to perform an informed search of their environment for an arbitrary object. However, such zer…

cs.RO2025

ViSA-Flow: Accelerating Robot Skill Learning via Large-Scale Video Semantic Action Flow

Changhe Chen, Quantao Yang, Xiaohao Xu +2

One of the central challenges preventing robots from acquiring complex manipulation skills is the prohibitive cost of collecting large-scale robot demonstrations. In contrast, huma…

cs.RO2025

FLoRA: Sample-Efficient Preference-based RL via Low-Rank Style Adaptation of Reward Functions

Daniel Marta, Simon Holk, Miguel Vasco +6

Preference-based reinforcement learning (PbRL) is a suitable approach for style adaptation of pre-trained robotic behavior: adapting the robot's policy to follow human user prefere…

cs.RO2025

One Map to Find Them All: Real-time Open-Vocabulary Mapping for Zero-shot Multi-Object Navigation

Finn Lukas Busch, Timon Homberger, Jesús Ortega-Peimbert +2

The capability to efficiently search for objects in complex environments is fundamental for many real-world robot applications. Recent advances in open-vocabulary vision models hav…