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Enhancing Lunar Reconnaissance Orbiter Images via Multi-Frame Super Resolution for Future Robotic space Missions

IEEE robotics AND automation LETTERS 2021年第4期6卷 7729-7735页

作者： Delgado-Centeno, J. I. Sanchez-Cuevas, P. J. Martinez, C. Olivares-Mendez, M. A. Univ Luxembourg SnT Interdisciplinary Ctr Secur Reliabil & Trust Space Robot Res Grp SpaceR L-1855 Luxembourg Luxembourg

This paper presents a novel application of a Multi-frame Super Resolution (MFSR) method for lunar surface imagery called Lunar HighRes-net (L-HRN). In this work, we adapted and used NASA's Lunar Reconnaissance Orbiter (LRO) image database to train the Deep Learning architecture for image super resolution. Additionally, we also gathered an artificial image dataset from our virtual Moon to improve the amount of input data in the neural network training process. The network's architecture follows a standard MFSR algorithm that was enhanced for this specific use case. The proposed MFSR method has been evaluated using the well-known peak signal-to-noise ratio (PSNR) metric against other generic super-resolution methods of the state of the art. This work aims to improve environmental knowledge about the lunar surface to enhance future autonomous robots capabilities on the surface of the Moon.

关键词： space vehicles Robots Training space robotics and automation aerial and field robotics

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Position Regulation of a Conductive Nonmagnetic Object With Two Stationary Rotating-Magnetic-Dipole Field Sources

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IEEE TRANSACTIONS ON robotics 2024年 40卷 4635-4647页

作者： Dalton, Devin K. Tabor, Griffin F. Hermans, Tucker Abbott, Jake J. Univ Utah Robot Ctr Salt Lake City UT 84112 USA Univ Utah Dept Mech Engn Salt Lake City UT 84112 USA United States Air Force Air Force Nucl Weap Ctr Albuquerque NM 87117 USA Kahlert Sch Comp Salt Lake City UT 84112 USA NVIDIA Seattle WA 98052 USA

Eddy currents induced by rotating magnetic dipole fields can produce forces and torques that enable dexterous manipulation of conductive nonmagnetic objects. This paradigm shows promise for application in the remediation of space debris. The induced force from each rotating-magnetic-dipole field source always includes a repulsive component, suggesting that the object should be surrounded by field sources to some degree to ensure the object does not leave the dexterous workspace during manipulation. In this article, we show that it is possible to fully control the position of an object in a workspace near the midpoint between just two stationary field sources. A given position controller requires a low-level force controller. We propose two new force controllers, and compare them with the state-of-the-art method from the literature. One of the new force controllers is particularly good at not inducing parasitic torques, which is hypothesized to be beneficial for future tasks manipulating and detumbling rotating resident space objects. We perform experimental verification using numerical and physical simulators of microgravity.

关键词： Force Torque Robots Robot kinematics Magnetic fields Vectors Regulation Manipulation planning motion control space robotics and automation

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MLNav: Learning to Safely Navigate on Martian Terrains

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IEEE robotics AND automation LETTERS 2022年第2期7卷 5461-5468页

作者： Daftry, Shreyansh Abcouwer, Neil Del Sesto, Tyler Venkatraman, Siddarth Song, Jialin Igel, Lucas Byon, Amos Rosolia, Ugo Yue, Yisong Ono, Masahiro Inst Technol Jet Prop Lab Pasadena CA 91109 USA Manipal Inst Technol Manipal 91109 Karnataka India Inst Technol Pasadena CA 91109 USA MIT Pittsburgh PA 15213 USA

We present MLNav, a learning-enhanced path planning framework for safety-critical and resource-limited systems operating in complex environments, such as rovers navigating on Mars. MLNav makes judicious use of machine learning to enhance the efficiency of path planning while fully respecting safety constraints. In particular, the dominant computational cost in such safety-critical settings is running a model-based safety checker on the proposed paths. Our learned search heuristic can simultaneously predict the feasibility for all path options in a single run, and the model-based safety checker is only invoked on the top-scoring paths. We validate in high-fidelity simulations using both real Martian terrain data collected by the Perseverance rover, as well as a suite of challenging synthetic terrains. Our experiments show that: (i) compared to the baseline ENav path planner on board the Perserverance rover, MLNav can provide a significant improvement in multiple key metrics, such as a 10x reduction in collision checks when navigating real Martian terrains, despite being trained with synthetic terrains;and (ii) MLNav can successfully navigate highly challenging terrains where the baseline ENav fails to find a feasible path before timing out.

关键词： Integrated planning and learning motion and path planning space robotics and automation

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Transformable Nano Rover for space Exploration

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IEEE robotics AND automation LETTERS 2024年第4期9卷 3139-3146页

作者： Hirano, Daichi Inazawa, Mariko Sutoh, Masataku Sawada, Hirotaka Kawai, Yuta Nagata, Masaharu Sakoda, Gen Yoneda, Yousuke Watanabe, Kimitaka Japan Aerosp Explorat Agcy Res & Dev Directorate Tsukuba 3058505 Japan Japan Aerosp Explorat Agcy Space Explorat Innovat Hub Ctr Sagamihara 2525210 Japan Japan Aerosp Explorat Agcy Human Spaceflight Technol Directorate Tsukuba 3058505 Japan Sony Grp Corp Exploratory Deployment Grp Tokyo 1418610 Japan TOMY Co Ltd Technol Dev Div Tokyo 1258503 Japan Doshisha Univ Fac Life & Med Sci Kyoto 6100394 Japan

This letter introduces a novel nano rover designed to transform its shape for efficient movement on lunar surfaces. The rover, resembling a compact ball, has a diameter of roughly 80 mm and a mass around 250 g. Its transformational mechanism allows for compactness during planetary transportation, with enhanced mobility achieved through the use of extendable wheels, a tail stabilizer, and cameras. To traverse soft terrains efficiently, the rover utilizes an eccentric wheel mechanism, offering two distinct movement modes based on wheel synchronization. This mechanism provides a locomotion velocity of 20 mm/s or more on a flat surface. Moreover, it features onboard image processing to detect spacecraft shielded by Multi-Layer Insulation (MLI) films, facilitating autonomous control and selective image transmission. This rover has been deployed in a real space mission, having been mounted on a lunar lander. This letter presents the design specifics of this transformable rover and results from field tests simulating lunar conditions. These tests affirmed the efficacy of the proposed motion mechanism and onboard image processing.

关键词： space robotics and automation wheeled robots micro/nano robots computer vision for automation vision-based navigation

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Enhancing Rover Teleoperation on the Moon With Proprioceptive Sensors and Machine Learning Techniques

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IEEE robotics AND automation LETTERS 2022年第4期7卷 11434-11441页

作者： Coloma, Sofia Martinez, Carol Yalcin, Baris Can Olivares-Mendez, Miguel A. Univ Luxembourg Interdisciplinary Res Ctr Secur Reliabil & Trust Space Robot SpaceR Res Grp L-1854 Esch Sur Alzette Luxembourg

Geological formations, environmental conditions, and soil mechanics frequently generate undesired effects on rovers' mobility, such as slippage or sinkage. Underestimating these undesired effects may compromise the rovers' operation and lead to a premature end of the mission. Minimizing mobility risks becomes a priority for colonising the Moon and Mars. However, addressing this challenge cannot be treated equally for every celestial body since the control strategies may differ;e.g. the low latency Earth-Moon communication allows constant monitoring and controls, something not feasible on Mars. This letter proposes a Hazard Information System (HIS) that estimates the rover's mobility risks (e.g. slippage) using proprioceptive sensors and Machine Learning (supervised and unsupervised). A Graphical User Interface was created to assist human-teleoperation tasks by presenting mobility risk indicators. The system has been developed and evaluated in the lunar analogue facility (LunaLab) at the University of Luxembourg. A real rover and eight participants were part of the experiments. Results demonstrate the benefits of the HIS in the decision-making processes of the operator's response to overcome hazardous situations.

关键词： Machine learning for robot control space robotics and automation telerobotics and teleoperation

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Performance Indicators for Wheeled Robots Traversing Obstacles

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IEEE robotics AND automation LETTERS 2020年第2期5卷 2881-2888页

作者： Nowac, William Gonzalez, Francisco MacMahon, Sadhbh Kovecses, Jozsef McGill Univ Dept Mech Engn Montreal PQ H3A 0G4 Canada McGill Univ Ctr Intelligent Machines Montreal PQ H3A 0G4 Canada Univ A Coruna Lab Ingn Mecan Ferrol 15403 Spain MDA Corp Brampton ON L6S 4J3 Canada

An important element of wheeled robot operations on uneven and unstructured terrain is the ability to overcome obstacles. In this letter, we deal with a part of this obstacle negotiation problem. We particularly investigate the ability of a wheeled robot, originating from its mechanical design, to successfully negotiate an obstacle. The work reported primarily investigates how the mechanism topologies and the resulting mass and inertia distributions influence obstacle negotiation. The kinematics of the obstacle and ground contact is described using the variables that represent the degrees of freedom of the articulated mechanical system of the robot;this enables the study of the effect of the robot topology on the contact dynamics. Based on this we develop a dynamics formulation that allows us to propose performance indicators to characterize the ability of the wheeled robot to overcome obstacles. This formulation accounts for the unilateral nature of interaction between robot, obstacle, and ground. We illustrate the work with simulation and experimental results.

关键词： Wheeled robots dynamics space robotics and automation contact modelling motion control

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Feature-Based Scanning LiDAR-Inertial Odometry Using Factor Graph Optimization

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IEEE robotics AND automation LETTERS 2023年第6期8卷 3374-3381页

作者： Setterfield, Timothy P. Hewitt, Robert A. Espinoza, Antonio Teran Chen, Po-Ting CALTECH Jet Prop Lab Pasadena CA 91109 USA MIT Cambridge MA 02139 USA

Localization of a mobile robot in the absence of an absolute position sensor often relies on techniques such as visual or lidar-inertial odometry. While lidar has many advantages, the most capable sensors use scanning mechanisms, leading to motion-distorted scans. Previous strategies used to account for robot motion when performing state estimation and outlier rejection have drawbacks for use on highly dynamic, resource-constrained robots such as spacecraft during descent and landing. In this letter we develop a novel probabilistic factor for the inclusion of scanning lidar features, and an accompanying outlier rejection methodology. By using well-established, efficient feature tracking techniques, our image processing front end is both reliable and amenable to FPGA implementation, both of which are critical for operation on a spacecraft. We demonstrate our technique on a dataset from simulated planetary descent and landing. The results show that our system can be used to perform accurate lidar-inertial odometry, even in highly dynamic scenarios.

关键词： Laser radar Distortion Extraterrestrial measurements Feature extraction Dynamics Cameras Robot sensing systems Lidar-inertial odometry localization space robotics and automation

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Material-Robot System for Assembly of Discrete Cellular Structures

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IEEE robotics AND automation LETTERS 2019年第4期4卷 4019-4026页

作者： Jenett, Benjamin Abdel-Rahman, Amira Cheung, Kenneth Gershenfeld, Neil MIT Ctr Bits & Atoms 77 Massachusetts Ave Cambridge MA 02139 USA NASA Ames Res Ctr Intelligent Syst Div Code TI Mountain View CA 94035 USA

We present a material-robot system consisting of mobile robots that can assemble discrete cellular structures. We detail themanufacturing of cuboctahedral unit cells, termed voxels, which passively connect to neighboring voxels with magnets. We then describe "relative" robots that can locomote on, transport, and place voxels. These robots are designed relative to and in coordination with the cellular structure-the geometry of the voxel informs the robot's global geometric configuration, local mechanisms, and end effectors, and robotic assembly features are designed into the voxels. We describe control strategies for determining build sequence, robot path planning, discretemotion control, and feedback, integrated within a custom software environment for simulating and executing a single or multi-robot construction. We use this material-robot system to build several types of structures, such as one-dimensional (1-D) beams, 2-D plates, and 3-D enclosures. The robots can navigate and assemble structures with minimal feedback, relying on voxel-sized resolution to achieve successful global positioning. We show a multi-robot assembly to increase the throughput and expand system capability using a deterministic centralized control strategy.

关键词： Assembly space robotics and automation path planning for multiple mobile robots or agents

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Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments

Gaussian Process Gradient Maps for Loop-Closure Detection in...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Le Gentil, Cedric Vayugundla, Mallikarjuna Giubilato, Riccardo Stuerzl, Wolfgang Vidal-Calleja, Teresa Triebel, Rudolph Univ Technol Sydney Fac Engn & IT Ctr Autonomous Syst Sydney NSW Australia German Aerosp Ctr Inst Robot & Mechatron Cologne Germany Tech Univ Munich TUM Dept Comp Sci Munich Germany

ISBN: (纸本)9781728162126

The ability to recognize previously mapped locations is an essential feature for autonomous systems. Unstructured planetary-like environments pose a major challenge to these systems due to the similarity of the terrain. As a result, the ambiguity of the visual appearance makes state-of-the-art visual place recognition approaches less effective than in urban or man-made environments. This paper presents a method to solve the loop closure problem using only spatial information. The key idea is to use a novel continuous and probabilistic representations of terrain elevation maps. Given 3D point clouds of the environment, the proposed approach exploits Gaussian Process (GP) regression with linear operators to generate continuous gradient maps of the terrain elevation information. Traditional image registration techniques are then used to search for potential matches. Loop closures are verified by leveraging both the spatial characteristic of the elevation maps (SE(2) registration) and the probabilistic nature of the GP representation. A submap-based localization and mapping framework is used to demonstrate the validity of the proposed approach. The performance of this pipeline is evaluated and benchmarked using real data from a rover that is equipped with a stereo camera and navigates in challenging, unstructured planetary-like environments in Morocco and on Mt. Etna.

关键词： Localization space robotics and automation Multi-Modal Perception Visual-Based Navigation

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Multi-Modal Loop Closing in Unstructured Planetary Environments with Visually Enriched Submaps

Multi-Modal Loop Closing in Unstructured Planetary Environme...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Giubilato, Riccardo Vayugundla, Mallikarjuna Stuerzl, Wolfgang Schuster, Martin J. Wedler, Armin Triebel, Rudolph German Aerosp Ctr DLR Inst Robot & Mechatron Munchener Str 20 D-82234 Wessling Germany

ISBN: (纸本)9781665417143

Future planetary missions will rely on rovers that can autonomously explore and navigate in unstructured environments. An essential element is the ability to recognize places that were already visited or mapped. In this work, we leverage the ability of stereo cameras to provide both visual and depth information, guiding the search and validation of loop closures from a multi-modal perspective. We propose to augment submaps that are created by aggregating stereo point clouds, with visual keyframes. Point clouds matches are found by comparing CSHOT descriptors and validated by clustering, while visual matches are established by comparing keyframes using Bag-of-Words (BoW) and ORB descriptors. The relative transformations resulting from both keyframe and point cloud matches are then fused to provide pose constraints between submaps in our graph-based SLAM framework. Using the LRU rover, we performed several tests in both an indoor laboratory environment as well as a challenging planetary analog environment on Mount Etna, Italy, consisting of areas where either keyframes or point clouds alone failed to provide adequate matches demonstrating the benefit of the proposed multi-modal approach.

关键词： Localization space robotics and automation Multi-modal Perception

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