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Chien SA, Visentin G, Basich C. Exploring beyond Earth using space robotics. Sci Robot 2024; 9:eadi6424. [PMID: 38896718 DOI: 10.1126/scirobotics.adi6424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 05/21/2024] [Indexed: 06/21/2024]
Abstract
Robotic spacecraft enable exploration of our Solar System beyond our human presence. Although spacecraft have explored every planet in the Solar System, the frontiers of space robotics are at the cutting edge of landers, rovers, and now atmospheric explorers, where robotic spacecraft must interact intimately with their environment to explore beyond the reach of flyby and orbital remote sensing. Here, we describe the tremendous growth in space robotics missions in the past 7 years, with many new entities participating in missions to the surface of the Moon, Mars, and beyond. We also describe the recent development of aerial missions to planets and moons, as exemplified by the Ingenuity helicopter on Mars and the Dragonfly mission to Titan. We focus on suborbital robotics-landers, rovers, and aerial vehicles-with associated challenges in sensing, manipulation, mobility, and system-level autonomy.
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Affiliation(s)
- Steve A Chien
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Gianfranco Visentin
- European Space Research and Technology Centre, European Space Agency, Noordwijk, Netherlands
| | - Connor Basich
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
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Sanchez-Cubillo J, Del Ser J, Martin JL. Toward Fully Automated Inspection of Critical Assets Supported by Autonomous Mobile Robots, Vision Sensors, and Artificial Intelligence. SENSORS (BASEL, SWITZERLAND) 2024; 24:3721. [PMID: 38931502 PMCID: PMC11207468 DOI: 10.3390/s24123721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 06/02/2024] [Accepted: 06/04/2024] [Indexed: 06/28/2024]
Abstract
Robotic inspection is advancing in performance capabilities and is now being considered for industrial applications beyond laboratory experiments. As industries increasingly rely on complex machinery, pipelines, and structures, the need for precise and reliable inspection methods becomes paramount to ensure operational integrity and mitigate risks. AI-assisted autonomous mobile robots offer the potential to automate inspection processes, reduce human error, and provide real-time insights into asset conditions. A primary concern is the necessity to validate the performance of these systems under real-world conditions. While laboratory tests and simulations can provide valuable insights, the true efficacy of AI algorithms and robotic platforms can only be determined through rigorous field testing and validation. This paper aligns with this need by evaluating the performance of one-stage models for object detection in tasks that support and enhance the perception capabilities of autonomous mobile robots. The evaluation addresses both the execution of assigned tasks and the robot's own navigation. Our benchmark of classification models for robotic inspection considers three real-world transportation and logistics use cases, as well as several generations of the well-known YOLO architecture. The performance results from field tests using real robotic devices equipped with such object detection capabilities are promising, and expose the enormous potential and actionability of autonomous robotic systems for fully automated inspection and maintenance in open-world settings.
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Affiliation(s)
| | - Javier Del Ser
- TECNALIA, Basque Research & Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain;
- Bilbao School of Engineering, University of the Basque Country (UPV/EHU), 48013 Bilbao, Bizkaia, Spain
| | - José Luis Martin
- TECNALIA, Basque Research & Technology Alliance (BRTA), 48160 Derio, Bizkaia, Spain;
- Bilbao School of Engineering, University of the Basque Country (UPV/EHU), 48013 Bilbao, Bizkaia, Spain
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Sands T. Bio-Inspired Space Robotic Control Compared to Alternatives. Biomimetics (Basel) 2024; 9:108. [PMID: 38392155 PMCID: PMC11154457 DOI: 10.3390/biomimetics9020108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 02/02/2024] [Accepted: 02/07/2024] [Indexed: 02/24/2024] Open
Abstract
Controlling robots in space with necessarily low material and structural stiffness is quite challenging at least in part due to the resulting very low structural resonant frequencies or natural vibration. The frequencies are sometimes so low that the very act of controlling the robot with medium or high bandwidth controllers leads to excitation of resonant vibrations in the robot appendages. Biomimetics or biomimicry emulates models, systems, and elements of nature for solving such complex problems. Recent seminal publications have re-introduced the viability of optimal command shaping, and one recent instantiation mimics baseball pitching to propose control of highly flexible space robots. The readership will find a perhaps dizzying array of thirteen decently performing alternatives in the literature but could be left bereft selecting a method(s) deemed to be best suited for a particular application. Bio-inspired control of space robotics is presented in a quite substantial (perhaps not comprehensive) comparison, and the conclusions of this study indicate the three top performing methods based on minimizing control effort (i.e., fuel) usage, tracking error mean, and tracking error deviation, where 96%, 119%, and 80% performance improvement, respectively, are achieved.
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Affiliation(s)
- Timothy Sands
- Department of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853, USA;
- Department of Mechanical and Aerospace Engineering, Naval Postgraduate School, Monterey, CA 93943, USA
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Pomares J, Felicetti L, Varagnolo D. Editorial: Multi-robot systems for space applications. Front Robot AI 2023; 10:1253381. [PMID: 37559570 PMCID: PMC10407796 DOI: 10.3389/frobt.2023.1253381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 07/14/2023] [Indexed: 08/11/2023] Open
Affiliation(s)
- Jorge Pomares
- Department of Physics, Systems Engineering and Signal Theory, University of Alicante, Alicante, Spain
| | - Leonard Felicetti
- School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, United Kingdom
| | - Damiano Varagnolo
- Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Information Engineering, University of Padova, Padova, Italy
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Kalaycioglu S, De Ruiter A. Passivity based nonlinear model predictive control (PNMPC) of multi-robot systems for space applications. Front Robot AI 2023; 10:1181128. [PMID: 37533425 PMCID: PMC10393258 DOI: 10.3389/frobt.2023.1181128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 05/09/2023] [Indexed: 08/04/2023] Open
Abstract
In the past 2 decades, there has been increasing interest in autonomous multi-robot systems for space use. They can assemble space structures and provide services for other space assets. The utmost significance lies in the performance, stability, and robustness of these space operations. By considering system dynamics and constraints, the Model Predictive Control (MPC) framework optimizes performance. Unlike other methods, standard MPC can offer greater robustness due to its receding horizon nature. However, current literature on MPC application to space robotics primarily focuses on linear models, which is not suitable for highly non-linear multi-robot systems. Although Nonlinear MPC (NMPC) shows promise for free-floating space manipulators, current NMPC applications are limited to unconstrained non-linear systems and do not guarantee closed-loop stability. This paper introduces a novel approach to NMPC using the concept of passivity to multi-robot systems for space applications. By utilizing a passivity-based state constraint and a terminal storage function, the proposed PNMPC scheme ensures closed-loop stability and a superior performance. Therefore, this approach offers an alternative method to the control Lyapunov function for control of non-linear multi-robot space systems and applications, as stability and passivity exhibit a close relationship. Finally, this paper demonstrates that the benefits of passivity-based concepts and NMPC can be combined into a single NMPC scheme that maintains the advantages of each, including closed-loop stability through passivity and good performance through one-line optimization in NMPC.
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Raisi M, Noohian A, Fallah S. A fault-tolerant and robust controller using model predictive path integral control for free-flying space robots. Front Robot AI 2022; 9:1027918. [PMID: 36569592 PMCID: PMC9768324 DOI: 10.3389/frobt.2022.1027918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 11/23/2022] [Indexed: 12/12/2022] Open
Abstract
The use of manipulators in space missions has become popular, as their applications can be extended to various space missions such as on-orbit servicing, assembly, and debris removal. Due to space reachability limitations, such robots must accomplish their tasks in space autonomously and under severe operating conditions such as the occurrence of faults or uncertainties. For robots and manipulators used in space missions, this paper provides a unique, robust control technique based on Model Predictive Path Integral Control (MPPI). The proposed algorithm, named Planner-Estimator MPPI (PE-MPPI), comprises a planner and an estimator. The planner controls a system, while the estimator modifies the system parameters in the case of parameter uncertainties. The performance of the proposed controller is investigated under parameter uncertainties and system component failure in the pre-capture phase of the debris removal mission. Simulation results confirm the superior performance of PE-MPPI against vanilla MPPI.
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Affiliation(s)
- Mehran Raisi
- Connected and Autonomous Vehicles Laboratory, School of Mechanical Engineering Sciences, University of Surrey, Guildford, England
| | - Amirhossein Noohian
- Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
| | - Saber Fallah
- Connected and Autonomous Vehicles Laboratory, School of Mechanical Engineering Sciences, University of Surrey, Guildford, England,*Correspondence: Saber Fallah,
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Barajas C, Del Vecchio D. Synthetic biology by controller design. Curr Opin Biotechnol 2022; 78:102837. [PMID: 36343564 DOI: 10.1016/j.copbio.2022.102837] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 02/26/2022] [Accepted: 10/07/2022] [Indexed: 11/06/2022]
Abstract
Natural biological systems display complex regulation and synthetic biomolecular systems have been used to understand their natural counterparts and to parse sophisticated regulations into core design principles. At the same time, the engineering of biomolecular systems has unarguable potential to transform current and to enable new, yet-to-be-imagined, biotechnology applications. In this review, we discuss the progression of control systems design in synthetic biology, from the purpose of understanding the function of naturally occurring regulatory motifs to that of creating genetic circuits whose function is sufficiently robust for biotechnology applications.
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Affiliation(s)
- Carlos Barajas
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Domitilla Del Vecchio
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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Application of bidirectional rapidly exploring random trees (BiRRT) algorithm for collision-free trajectory planning of free-floating space manipulator. ROBOTICA 2022. [DOI: 10.1017/s0263574722000935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Abstract
On-orbit servicing and active debris removal missions will rely on the use of unmanned satellite equipped with a manipulator. Capture of the target object will be the most challenging phase of these missions. During the capture manoeuvre, the manipulator must avoid collisions with elements of the target object (e.g., solar panels). The dynamic equations of the satellite-manipulator system must be used during the trajectory planning because the motion of the manipulator influences the position and orientation of the satellite. In this paper, we propose application of the bidirectional rapidly exploring random trees (BiRRT) algorithm for planning a collision-free trajectory of a manipulator mounted on a free-floating satellite. A new approach based on pseudo-velocities method (PVM) is used for construction of nodes of the trajectory tree. Initial nodes of the second tree are selected from the set of potential final configurations of the system. The proposed method is validated in numerical simulations performed for a planar case (3-DoF manipulator). The obtained results are compared with the results obtained with two other trajectory planning methods based on the RRT algorithm. It is shown that in a simple test scenario, the proposed BiRRT PVM algorithm results in a lower manipulator tip position error. In a more difficult test scenario, only the proposed method was able to find a solution. Practical applicability of the BiRRT PVM method is demonstrated in experiments performed on a planar air-bearing microgravity simulator where the trajectory is realised by a manipulator mounted on a mock-up of the free-floating servicing satellite.
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Time delay estimation-based reactionless augmented adaptive sliding mode control of a space manipulator’s pregrasping a target. ROBOTICA 2022. [DOI: 10.1017/s0263574722000108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Abstract
Reaction null space (RNS) planning and control of a planar three-link space manipulator’s pregrasping a spinning target are studied. First, the Lagrange dynamic model of the manipulator was established. Second, the RNS motion planning algorithm was derived, and the vector norm constraint algorithm of RNS planning was addressed to ensure certain joint angular acceleration constraints were satisfied. Furthermore, an augmented adaptive sliding mode controller based on time delay estimation (TDE) was proposed. This controller estimated the unknowns of the system by TDE technology, in which accurate and complete dynamics were not required, and an adaptive TDE was introduced to decrease the estimation errors and avoid serious chattering. Finally, numerical simulations were carried out to verify the effectiveness of the proposed RNS planning and control algorithm.
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Si W, Wang N, Li Q, Yang C. A Framework for Composite Layup Skill Learning and Generalizing Through Teleoperation. Front Neurorobot 2022; 16:840240. [PMID: 35250529 PMCID: PMC8896344 DOI: 10.3389/fnbot.2022.840240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 01/06/2022] [Indexed: 11/13/2022] Open
Abstract
In this article, an impedance control-based framework for human-robot composite layup skill transfer was developed, and the human-in-the-loop mechanism was investigated to achieve human-robot skill transfer. Although there are some works on human-robot skill transfer, it is still difficult to transfer the manipulation skill to robots through teleoperation efficiently and intuitively. In this article, we developed an impedance-based control architecture of telemanipulation in task space for the human-robot skill transfer through teleoperation. This framework not only achieves human-robot skill transfer but also provides a solution to human-robot collaboration through teleoperation. The variable impedance control system enables the compliant interaction between the robot and the environment, smooth transition between different stages. Dynamic movement primitives based learning from demonstration (LfD) is employed to model the human manipulation skills, and the learned skill can be generalized to different tasks and environments, such as the different shapes of components and different orientations of components. The performance of the proposed approach is evaluated on a 7 DoF Franka Panda through the robot-assisted composite layup on different shapes and orientations of the components.
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Affiliation(s)
- Weiyong Si
- Bristol Robotics Laboratory, Faculty of Environment and Technology, University of the West of England, Bristol, United Kingdom
| | - Ning Wang
- Bristol Robotics Laboratory, Faculty of Environment and Technology, University of the West of England, Bristol, United Kingdom
| | - Qinchuan Li
- Faculty of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, China
| | - Chenguang Yang
- Bristol Robotics Laboratory, Faculty of Environment and Technology, University of the West of England, Bristol, United Kingdom
- *Correspondence: Chenguang Yang
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Shrivastava A, Dalla VK, Dal PN. Space Debris Manipulation by Cooperative Redundant Planar Robots with Minimized Trajectory Error. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2022. [DOI: 10.1007/s13369-022-06573-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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