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Aerospace
Special Issues
Space Robotics and Embodied Intelligence: Advancing Autonomous Exploration
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Space Robotics and Embodied Intelligence: Advancing Autonomous Exploration

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Astronautics & Space Science".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 2624

Special Issue Editors

Dr. Deshan Meng

E-Mail Website
Guest Editor
School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen 518055, China
Interests: space robots; innovative design; multibody dynamics; intelligent control
Dr. Lei Yan

E-Mail Website
Guest Editor
School of Mechanical Engineering and Automation, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
Interests: dexterous manipulation; novel techniques and algorithms developed in several areas including motion planning, trajectory optimization and model-based control
Special Issues, Collections and Topics in MDPI journals
Dr. Linqi Ye

E-Mail Website
Guest Editor
School of Future Technology, Shanghai University, Shanghai 200444, China
Interests: robotics; embodied intelligence, and their combination with fine art

Special Issue Information

Dear Colleagues,

The development of space robotics technology is rapidly advancing, with a wide range of applications involving manned spaceflight, on-orbit services, large space structure assembly in orbit, planetary scientific exploration, and space resource development. The structure of space robots has evolved from traditional rigid structures to flexible or soft body structures, showing a trend toward the integration of rigid and soft characteristics. This diversity in structure enables space robots to adapt to more complex space environments and mission requirements. These new forms of space robots face technical challenges in terms of mechanism configuration, joint actuation, end-effector operation, perception and cognition, locomotion, dynamics, and control, which require new theories and technological innovations to address. To improve the efficiency and safety of robots operating in harsh space environments, it is increasingly important to empower space robots with artificial intelligence. The combination of space robots with AI large models and embodied intelligence technologies can enhance their autonomy, environmental perception capabilities, and decision-making abilities. This Special Issue encourages researchers, engineers, and scholars to submit their latest research results in this field, covering new space robot designs or corresponding methodologies, the application of artificial intelligence in space robots, and research methods and experimental validation related to space robot operations, to jointly promote the advancement of space robotics technology.

Dr. Deshan Meng
Dr. Lei Yan
Dr. Linqi Ye
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • space robotics
  • space manipulators
  • embodied intelligence
  • innovative design
  • trajectory optimization
  • perception and manipulation
  • intelligent control
  • human–robot interaction
  • on-orbit servicing
  • autonomous exploration

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Published Papers (2 papers)

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Research

22 pages, 10072 KiB  
Article
A Manipulability-Driven Method for Efficient Telescopic Motion Computation of Controllable Space Manipulator
by Shize Qin, Wang Lu, Tao Yang, Shoujun Zhao, Xiaoqi Li, Zelin Yang and Guangwei Yu
Aerospace 2025, 12(2), 129; https://doi.org/10.3390/aerospace12020129 - 8 Feb 2025
Viewed by 700
Abstract
The addition of telescopic joints will enhance the manipulator’s motion dexterity but increase the motion complexity, thereby potentially reducing the efficiency of motion planning. To address the issue, a manipulability priority principle is used to reduce the computational dimension, aiming to enhance computational [...] Read more.
The addition of telescopic joints will enhance the manipulator’s motion dexterity but increase the motion complexity, thereby potentially reducing the efficiency of motion planning. To address the issue, a manipulability priority principle is used to reduce the computational dimension, aiming to enhance computational efficiency. Firstly, an improved Monte Carlo algorithm combined with Weighted Ensemble Learning is proposed to rapidly obtain a well-distributed and information-complete reachable workspace under small-sample conditions. Then, all dexterous points are computed by the manipulability formula and the least squares algorithm is applied to obtain the boundary of the reachable workspace. Based on the boundary, a spatial quadratic surface-based segmentation algorithm is proposed to obtain the dexterous workspace corresponding to all dexterous points. Subsequently, the Telescopic Motion Computation (TMC) method is designed to transform the kinematics problem of a 9-DOF manipulator into a 7-DOF problem by precomputing the telescopic joint lengths, effectively reducing the computational time for inverse kinematics. Finally, simulations are performed to verify the effectiveness, dexterity, and efficiency of the TMC method. The results indicate that applying the TMC method to PInv, DLS, and PSO algorithms enhances the efficiency by 3.43, 3.53, and 3.64 times while maintaining the motion dexterity. Full article
(This article belongs to the Special Issue Space Robotics and Embodied Intelligence: Advancing Autonomous Exploration)
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16 pages, 28400 KiB  
Article
Compliance Control of a Cable-Driven Space Manipulator Based on Force–Position Hybrid Drive Mode
by Runhui Xiang, Hejie Xu, Xinliang Li, Xiaojun Zhu, Deshan Meng and Wenfu Xu
Aerospace 2025, 12(1), 69; https://doi.org/10.3390/aerospace12010069 - 19 Jan 2025
Viewed by 1151
Abstract
Multi-cable cooperative control is essential for cable-driven space manipulators to achieve in-orbit services such as fault spacecraft maintenance, fuel injection, on-orbit assembly, and orbital garbage removal. To prevent the cables from becoming slack or excessively tight, the force in each cable must be [...] Read more.
Multi-cable cooperative control is essential for cable-driven space manipulators to achieve in-orbit services such as fault spacecraft maintenance, fuel injection, on-orbit assembly, and orbital garbage removal. To prevent the cables from becoming slack or excessively tight, the force in each cable must be distributed appropriately. The force distribution among different cables requires real-time adjustments; otherwise, the system may become unstable. This paper proposes a compliance control method based on the force–position hybrid drive mode to address the challenges of multi-cable cooperative control. Firstly, the mapping relationship between the cable space and the joint space of the cable-driven space manipulator is established. Then, the force mapping relationship for this structure is derived. The control scheme categorizes the cables into two types: active-side cables and antagonistic-side cables. Position control and force control are implemented separately, significantly reducing the computational requirements and enhancing the overall performance of the control system. Finally, the feasibility of the proposed algorithm is demonstrated through simulations and compared with the PID control method. When tracking the same trajectory, the proposed method reduces the tracking error by 49.14% and the maximum force by 58.58% compared to the PID control method, effectively addressing the problem of force distribution in multi-rope coordinated control. Full article
(This article belongs to the Special Issue Space Robotics and Embodied Intelligence: Advancing Autonomous Exploration)
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