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Assembling Solar Panels by Dual Robot Arms Towards Full Autonomous Lunar Base Construction

Luca Nunziante, Kentaro Uno, Gustavo H. Diaz, Shreya Santra, Alessandro De Luca, Kazuya Yoshida

TL;DR

This work tackles autonomous lunar-base construction by enabling two robotic arms to assemble modular solar panels in situ. It fuses a perception pipeline based on YOLOv8.1 with oriented bounding boxes and a control framework that combines impedance control, force control, and nonlinear Model Predictive Control to achieve collision-free gripping and assembly. A key novelty is the integrated pipeline that maps 2D detections to a 3D end-effector pose $r_d \in \mathbb{R}^6$ via stereo depth and then guides manipulation through an NMPC-enabled trajectory and a robust, axis-angle–based orientation scheme. Real-world experiments with mock-up panels demonstrate the ability of dual manipulators to localize, connect arbitrarily placed panels, and perform autonomous assembly, highlighting the practical viability for scalable lunar-base infrastructure.

Abstract

Since the successful Apollo program, humanity is once again aiming to return to the Moon for scientific discovery, resource mining, and inhabitation. Upcoming decades focus on building a lunar outpost, with robotic systems playing a crucial role to safely and efficiently establish essential infrastructure such as solar power generating towers. Similar to the construction of the International Space Station (ISS), shipping necessary components via modules and assembling them in situ should be a practical scenario. In this context, this paper focuses on the integration of vision, control, and hardware systems within an autonomous sequence for a dual-arm robot system. We explore a perception and control pipeline specifically designed for assembling solar panel modules, one of the benchmark tasks. Ad hoc hardware was designed and tested in real-world experiments. A mock-up of modular solar panels and active-passive connectors are employed, with the control of this grappling fixture integrated into the proposed pipeline. The successful implementation of our method demonstrates that the two robot manipulators can effectively connect arbitrarily placed panels, highlighting the seamless integration of vision, control, and hardware systems in complex space applications.

Assembling Solar Panels by Dual Robot Arms Towards Full Autonomous Lunar Base Construction

TL;DR

This work tackles autonomous lunar-base construction by enabling two robotic arms to assemble modular solar panels in situ. It fuses a perception pipeline based on YOLOv8.1 with oriented bounding boxes and a control framework that combines impedance control, force control, and nonlinear Model Predictive Control to achieve collision-free gripping and assembly. A key novelty is the integrated pipeline that maps 2D detections to a 3D end-effector pose via stereo depth and then guides manipulation through an NMPC-enabled trajectory and a robust, axis-angle–based orientation scheme. Real-world experiments with mock-up panels demonstrate the ability of dual manipulators to localize, connect arbitrarily placed panels, and perform autonomous assembly, highlighting the practical viability for scalable lunar-base infrastructure.

Abstract

Since the successful Apollo program, humanity is once again aiming to return to the Moon for scientific discovery, resource mining, and inhabitation. Upcoming decades focus on building a lunar outpost, with robotic systems playing a crucial role to safely and efficiently establish essential infrastructure such as solar power generating towers. Similar to the construction of the International Space Station (ISS), shipping necessary components via modules and assembling them in situ should be a practical scenario. In this context, this paper focuses on the integration of vision, control, and hardware systems within an autonomous sequence for a dual-arm robot system. We explore a perception and control pipeline specifically designed for assembling solar panel modules, one of the benchmark tasks. Ad hoc hardware was designed and tested in real-world experiments. A mock-up of modular solar panels and active-passive connectors are employed, with the control of this grappling fixture integrated into the proposed pipeline. The successful implementation of our method demonstrates that the two robot manipulators can effectively connect arbitrarily placed panels, highlighting the seamless integration of vision, control, and hardware systems in complex space applications.
Paper Structure (7 sections, 3 equations, 3 figures)

This paper contains 7 sections, 3 equations, 3 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Perception
  4. Control
  5. Method
  6. Approaching and Grasping
  7. Collision-free lifting

Figures (3)

  • Figure 1: Overall hardware setup (top) and functional scheme to illustrate the integration and interaction of the perception and control modules (bottom).
  • Figure 2: Flowchart of the assembly pipeline. Impedance control is utilized to adjust to the pushed force when grasping the panels as well as inserting one panel into the other. NMPC allows controlling the panel picking up trajectory avoiding the collision with the surrounding environment.
  • Figure 3: Result of the inference made by the YOLO model in challenging lighting conditions: dark assumed in Lunar environment. From the patch detection we retrieve the panel orientation, while the connector detection provides the desired position for the end-effector.