AimBot：一种增强视觉运动策略空间感知的简易辅助视觉提示

摘要

本文提出了一种轻量级视觉增强技术——AimBot，通过提供明确的空间线索来提升机器人操作中的视觉运动策略学习。AimBot在多个视角的RGB图像上叠加射击线和瞄准镜十字线，为末端执行器状态编码提供辅助视觉引导。这些叠加信息由深度图像、相机外参及当前末端执行器姿态计算得出，明确传达了夹爪与场景中物体间的空间关系。AimBot引入的计算开销极低（小于1毫秒），且无需改变模型架构，仅需将原始RGB图像替换为增强后的版本。尽管方法简单，实验结果表明，无论是在仿真还是真实环境中，AimBot均能持续提升多种视觉运动策略的性能，凸显了基于空间定位的视觉反馈的优势。

English

In this paper, we propose AimBot, a lightweight visual augmentation technique that provides explicit spatial cues to improve visuomotor policy learning in robotic manipulation. AimBot overlays shooting lines and scope reticles onto multi-view RGB images, offering auxiliary visual guidance that encodes the end-effector's state. The overlays are computed from depth images, camera extrinsics, and the current end-effector pose, explicitly conveying spatial relationships between the gripper and objects in the scene. AimBot incurs minimal computational overhead (less than 1 ms) and requires no changes to model architectures, as it simply replaces original RGB images with augmented counterparts. Despite its simplicity, our results show that AimBot consistently improves the performance of various visuomotor policies in both simulation and real-world settings, highlighting the benefits of spatially grounded visual feedback.

AimBot：一种增强视觉运动策略空间感知的简易辅助视觉提示

AimBot: A Simple Auxiliary Visual Cue to Enhance Spatial Awareness of Visuomotor Policies

摘要

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