# Mobile Manipulator for Autonomous Localization, Grasping and Precise Placement of Construction Material in a Semi-structured Environment

arXiv: https://arxiv.org/abs/2011.07972 · HTML: https://mlsanity.com/paper/2011.07972/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Nov 2020.

## Built on by (most cited first, 4 of 4)

- [MoManipVLA: Transferring Vision-language-action Models for General Mobile Manipulation](https://mlsanity.com/paper/2503.13446/) (2025)
- [Holistic Construction Automation with Modular Robots: From High-Level Task Specification to Execution](https://mlsanity.com/paper/2412.20867/) (2024)
- [A Reactive Framework for Whole-Body Motion Planning of Mobile Manipulators Combining Reinforcement Learning and SDF-Constrained Quadratic Programmi](https://mlsanity.com/paper/2503.23975/) (2025)
- [Tactile-based Reinforcement Learning for Adaptive Grasping under Observation Uncertainties](https://mlsanity.com/paper/2505.16167/) (2025)

## Abstract (arXiv)

Mobile manipulators have the potential to revolutionize modern agriculture, logistics and manufacturing. In this work, we present the design of a ground-based mobile manipulator for automated structure assembly. The proposed system is capable of autonomous localization, grasping, transportation and deployment of construction material in a semi-structured environment. Special effort was put into making the system invariant to lighting changes, and not reliant on external positioning systems. Therefore, the presented system is self-contained and capable of operating in outdoor and indoor conditions alike. Finally, we present means to extend the perceptive radius of the vehicle by using it in cooperation with an autonomous drone, which provides aerial reconnaissance. Performance of the proposed system has been evaluated in a series of experiments conducted in real-world conditions.