AimBot: A Simple Auxiliary Visual Cue to Enhance Spatial Awareness of
  Visuomotor Policies
Authors: name: Yinpei Dai, name: Jayjun Lee, name: Yichi Zhang, name: Ziqiao Ma, name: Jed Yang, name: Amir Zadeh, name: Chuan Li, name: Nima Fazeli, name: Joyce Chai

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.