Visual Prompting for Robotic Manipulation with Annotation-Guided Pick-and-Place Using ACT

arXiv:2508.08748 · cs.RO, cs.AI · Submitted 2026-08-18 · Read on arXiv

Muhammad A. Muttaqien, Tomohiro Motoda, Ryo Hanai, Yukiyasu Domae

cs.RO, cs.AI

Submitted: 2026-08-18

Updated: 2026-08-19

Code: https://github.com/isri-aist/RoboManipBaselines

Terminology

• Transformer — 19× in this paper · explained in 2 episodes
• Adaptability — 12× in this paper · explained in 1 episode
• Accuracy — 10× in this paper · explained in 1 episode
• Action Chunking — 10× in this paper · explained in 1 episode
• Action Chunking with Transformers — 5× in this paper
• Embodied AI — 4× in this paper · explained in 2 episodes
• Reinforcement Learning — 4× in this paper · explained in 4 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Depth Field of View — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Affordance — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Human-in-the-Loop — 1× in this paper · explained in 3 episodes
• Institute of Advanced Industrial Science and Technology — 1× in this paper
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes

Sources

• Robotic Grasping from Classical to Modern: A Survey
• Improved GQ-CNN: Deep Learning Model for Planning Robust Grasps
• PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

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