Long-Reach Robotic Manipulation for Assembly and Outfitting of Lunar Structures

Stanley Wang; Venny Kojouharov; Long Yin Chung; Daniel Morton; Mark Cutkosky

cs.ROMar 31, 2026

Long-Reach Robotic Manipulation for Assembly and Outfitting of Lunar Structures

Authors: Stanley Wang, Venny Kojouharov, Long Yin Chung, Daniel Morton, Mark Cutkosky

Organizations: Stanford University · All authors are with the Dept. of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.

Abstract

Future infrastructure construction on the lunar surface will require semi- or fully-autonomous operation from robots deployed at the build site. In particular, tasks such as electrical outfitting necessitate transport, routing, and fine manipulation of cables across large structures. To address this need, we present a compact and long-reach manipulator incorporating a deployable composite boom, capable of performing manipulation tasks across large structures and workspaces. We characterize the deflection, vibration, and blossoming characteristics inherent to the deployable structure, and present a manipulation control strategy to mitigate these effects. Experiments indicate an average endpoint accuracy error of less than 15 mm for boom lengths up to 1.8 m. We demonstrate the approach with a cable routing task to illustrate the potential for lunar outfitting applications that benefit from long reach.

Figures & tables

Fig. 1: Small mobile robots (green) equipped with long, extendable booms (red) can perform tasks that require a large workspace—such as cable stringing and assembly for lunar construction.

Fig. 2: (A) Overview of key hardware components in the long-reach manipulator design: shoulder base, deployable boom arm (0.2 - 3m), and dexterous wrist. (B) Mechanical characterizations of the boom’s uniaxial bending and free vibration effects. (C) Boom deployment blossoming effects.

Fig. 3: (A) Rigid kinematic model of the robot manipulator following an R-R-P-R-R-R architecture. (B) Additional augmentation transformation used to compensate for elastic boom deflection.

Fig. 4: Overview of the control framework. The robot follows task trajectories using visual end-effector localization and an augmented task-space kinematic model for closed-loop position control.

Fig. 5: Summary of tracking error across the robot workspace. (A) A $10\,\text{cm}\times 10\,\text{cm}$ square reference trajectory. The robot’s executed trajectories across trials are overlaid, and the maximum spatial error is visualized as a task tube. (B) All trajectories executed at $\theta=0^{\circ}$ for varying boom lengths (horizontal axis) and task speeds (vertical axis). Error increases with both parameters. (C) Interpolated 95th percentile isoline plot for $\theta=0^{\circ}$ . (D) Total robot workspace schematic showing boom length $d_{3}$ , pitch angle $\theta_{2}$ , and yaw $\theta_{1}$ with an error slice at 50 mm/s. (E) Interpolated error slices at $\theta\in[0^{\circ},90^{\circ}]$ for two speeds: 17 mm/s (slow) and 80 mm/s (fast). Errors increase with both pitch angle and extension, especially at higher speeds.

Fig. 6: Semi-autonomous cable routing task. (A) Four stages of the task motion primitive. (B) Robot autonomously performs this task primitive using visual servoing at four hooks at varying locations and orientations. Video available in supplementary material.

Hook	${\theta_{2}}$ ( ∘ )	$d_{3}$ (m)	$s^{*}$ (mm/s)	$e$ (mm)	$e_{meas}$ (mm)
1	35	1.27	55	15	14.8
2	24	1.78	19	15	11.4
3	13	1.07	70	15	14.1
4	31	1.55	25	15	10.9

TABLE I: Cable Routing Parameters and Errors at Each Hook

Robotic Manipulation

Robotic manipulation studies how robots perceive, plan, and control physical interactions to grasp, move, assemble, and use objects.

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Long-Reach Robotic Cleaning for Lunar Solar Arrays

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Commercial lunar activity is accelerating the need for reliable surface infrastructure and routine operations to keep it functioning. Maintenance tasks such as inspection, cleaning, dust mitigation, and minor repair are essential to preserve performance and extend system life. A specific application is the cleaning of lunar solar arrays. Solar arrays are expected to provide substantial fraction of lunar surface power and operate for months to years, supplying continuous energy to landers, habitats, and surface assets, making sustained output mission-critical. However, over time lunar dust accumulates on these large solar arrays, which can rapidly degrade panel output and reduce mission lifetime. We propose a small mobile robot equipped with a long-reach, lightweight deployable boom and interchangeable cleaning tool to perform gentle cleaning over meter-scale workspaces with minimal human involvement. Building on prior vision-guided long-reach manipulation, we add a compliant wrist with distal force sensing and a velocity-based admittance controller to regulate stable contact during surface cleaning. In preliminary benchtop experiments on a planar surface, the system maintained approximately 2 N normal force while executing a simple cleaning motion over boom lengths from 0.3 m to 1.0 m, with RMS force error of approximately 0.2 N after initial contact. These early results suggest that deployable long-reach manipulators are a promising architecture for robotic maintenance of lunar infrastructure such as solar arrays, radiators, and optical surfaces.

Abstract

Robotic Manipulation

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