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Ablation Study of Multimodal Perception, Language Grounding, and Control for Human-Robot Interaction in an Object Detection and Grasping Task

Summary

This paper presents a controlled ablation study of three key modules in a multimodal human-robot interaction system: the large language model for action extraction, the perception system for visual grounding, and the controller for motion execution. It compares three language models, five perception configurations, and three controllers, followed by a factorial study of the best combinations, aiming to identify which choices affect execution time versus success rate.

SourcearXiv RoboticsAuthor: Zi Tian, Guanting Shen
Ablation Study of Multimodal Perception, Language Grounding, and Control for Human-Robot Interaction in an Object Detection and Grasping Task
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[2605.00963] Ablation Study of Multimodal Perception, Language Grounding, and Control for Human-Robot Interaction in an Object Detection and Grasping Task

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Computer Science > Robotics

arXiv:2605.00963 (cs)

[Submitted on 1 May 2026]

Title:Ablation Study of Multimodal Perception, Language Grounding, and Control for Human-Robot Interaction in an Object Detection and Grasping Task

Authors:Zi Tian, Guanting Shen

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Abstract:This manuscript extends our previous multimodal human-robot interaction system by introducing a controlled ablation study of the three modules that most strongly influence end-to-end performance: the large language model used for action extraction, the perception system used for visual grounding, and the controller used for motion execution. The goal is not to redesign the full pipeline, but to isolate the contribution of each component under a common experimental protocol and then evaluate the best combinations end-to-end. We therefore compare three language models, five perception configurations, and three controllers, followed by a second-stage factorial study over the best candidates. The resulting analysis is intended to clarify which choices primarily affect execution time, which primarily affect success rate, and where the largest engineering gains are likely to come from in future revisions of the system.

Comments: 10 pages

Subjects:

Robotics (cs.RO); Artificial Intelligence (cs.AI)

Cite as: arXiv:2605.00963 [cs.RO]

(or arXiv:2605.00963v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2605.00963

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arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Guanting Shen [view email] [v1] Fri, 1 May 2026 15:04:53 UTC (175 KB)

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Key points and analysis

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Key points

  • Ablation study isolating three modules: LLM, perception, controller.
  • Comparison of 3 LLMs, 5 perception configurations, 3 controllers.
  • Factorial study of best candidates in second stage.
  • Clarifies factors affecting execution time and success rate.

Highlights and analysis are generated automatically and may contain errors. Check the original source.