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MLNav: Learning to Safely Navigate on Martian Terrains

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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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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Lunar Excavator Mission Operations using Dynamic Movement Primitives

Lunar Excavator Mission Operations using Dynamic Movement Pr...

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

作者： Cloud, Joseph M. Tram, Minh Q. Beksi, William J. DuPuis, Michael A. NASA John F Kennedy Space Ctr Adv Engn Dev Branch NE L6 Kennedy Space Ctr FL 32899 USA Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76013 USA

ISBN: (纸本)9781665491907

To support sustainable infrastructure on the Moon, NASA must leverage robots to extract lunar resources for in-situ processing and construction. As part of this effort, NASA is launching the in-situ resource utilization (ISRU) Pilot Excavator later this decade to validate a robotic regolith excavator based on the Regolith Advanced Surface Systems Operations Robot (RASSOR). RASSOR is designed to extract and transport regolith to meet the needs of ISRU architectures. During its mission, Pilot Excavator will be tasked with driving in test patterns to demonstrate the operational concept. One possible test pattern is a circular trajectory around the lander while avoiding surface hazards such as lunar rocks. To this end, we utilize dynamic movement primitives to represent navigation sequences as primitive trajectories. We introduce a novel obstacle avoidance parameter, which is configured to avoid rocks throughout testing exercises. We demonstrate the effectiveness our method in a newly developed simulation tool called the Simulated Excavation Environment for Lunar Operations (SEELO) using models based on the NASA RASSOR 2.0 excavator. Our results show that the robot is able to safety and robustly navigate the lunar surface with densely populated rock obstacles while retaining the desired circle pattern behavior.

关键词： space robotics and automation Learning from Demonstration Mining Robots

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Magnetic manipulation of unknown and complex conductive nonmagnetic objects with application in the remediation of space debris

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2024年

作者： Tabor, Griffin F. Pham, Lan N. Abbott, Jake J. Hermans, Tucker Univ Utah Robot Ctr Salt Lake City UT 84112 USA Univ Utah Kahlert Sch Comp Salt Lake City UT 84112 USA Univ Utah Dept Mech Engn Salt Lake City UT 84112 USA NVIDIA Seattle WA USA

This article extends recent work in magnetic manipulation of conductive, nonmagnetic objects using rotating magnetic dipole fields. Eddy-current-based manipulation provides a contact-free way to manipulate metallic objects. We are particularly motivated by the large amount of aluminum in space debris. We previously demonstrated dexterous manipulation of solid spheres with all object parameters known a priori. This work expands the previous model, which contained three discrete modes, to a continuous model that covers all possible relative positions of the manipulated spherical object with respect to the magnetic field source. We further leverage this new model to examine manipulation of spherical objects with unknown physical parameters by applying techniques from the online-optimization and adaptive-control literature. Our experimental results validate our new dynamics model, showing that we get improved performance compared to the previously proposed model, while also solving a simpler optimization problem for control. We further demonstrate the first physical magnetic manipulation of aluminum spheres, as previous controllers were only physically validated on copper spheres. We show that our adaptive control framework can quickly acquire useful object parameters when weakly initialized. Finally, we demonstrate that the spherical-object model can be used as an approximate model for adaptive control of nonspherical objects by performing magnetic manipulation of a variety of objects for which a spherical model is not an obvious approximation.

关键词： space robotics and automation dexterous manipulation model learning for control robust/adaptive control optimization and optimal control

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ReachBot: A Small Robot with Exceptional Reach for Rough Terrain 39

ReachBot: A Small Robot with Exceptional Reach for Rough Ter...

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IEEE International Conference on robotics and automation (ICRA)

作者： Chen, Tony G. Miller, Becky Winston, Crystal Schneider, Stephanie Bylard, Andrew Pavone, Marco Cutkosky, Mark R. Stanford Univ Dept Mech Engn Stanford CA 94305 USA Stanford Univ Dept Aeronaut & Astronaut Stanford CA 94305 USA

ISBN: (纸本)9781728196817

ReachBot is a new concept for planetary exploration, consisting of a small body and long, lightweight extending arms loaded primarily in tension. The arms are equipped with spined grippers for anchoring on rock surfaces. The design and testing of a planar prototype is presented here. Experiments with rock grasping and coordinated locomotion illustrate the advantages of low inertia passive grippers, triggered by impact and using stored mechanical energy for the internal force. Gripper design involves a trade-off among the range of possible grasp angles, maximum grasp force, required triggering force, and required reset force. The current prototype can pull with up to 8N when gripping volcanic rock, limited only by the strength of the 3D printed components. Calculations predict a maximum pull of 26N for the same spines and stronger materials.

关键词： Mobile Manipulation space robotics and automation Climbing Robots Grippers and Other End-Effectors Mechanism Design

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Compliant Floating-Base Control of space Robots

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IEEE robotics AND automation LETTERS 2021年第4期6卷 7485-7492页

作者： Giordano, Alessandro Massimo Calzolari, Davide De Stefano, Marco Mishra, Hrishik Ott, Christian Albu-Schaeffer, Alin German Aerosp Ctr DLR Inst Robot & Mechatron D-82234 Wessling Germany Tech Univ Munchen TUM Dept Informat D-85748 Garching Germany

This letter presents a compliant feedback controller of an arm-equipped spacecraft, which does not enforce requirements on the spacecraft position and attitude. The controller is applicable to the pre-contact, contact, and post-contact phases of a robotic operation. In contrast to conventional floating-base strategies, the controller eliminates the instability of the system during a steady contact, and thus can be used in realistic applications. The controller uses an external-internal transposed-Jacobian control for compliant regulation of the end-effector, together with regulation of the whole-body Center-of-Mass (CoM) and angular momentum for achieving post-contact stability, and force feedback for achieving a stable contact phase. The method is validated experimentally using a hardware-in-the-loop simulator composed of a seven degrees-of-freedom (DOF) arm mounted on a 6 DOF simulated spacecraft. Numerical simulations further validate the method considering a realistic thrusters system, measurement noise, and time delay.

关键词： space robotics and automation compliance and impedance control passivity motion control dynamics

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A Relative Dynamics Formulation for Hardware-in-the-Loop Simulation of On-Orbit Robotic Missions

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IEEE robotics AND automation LETTERS 2021年第2期6卷 3569-3576页

作者： Destefano, Marco Mishra, Hrishik Giordano, Alessandro M. Lampariello, Roberto Ott, Christian German Aerosp Ctr DLR Inst Robot & Mechatron D-82234 Wessling Germany

In this letter, we propose a novel method for the on-ground simulation of a space robotic mission, while exploiting a robotic hardware-in-the-loop facility. The simulated dynamics replicated by the robots are defined with respect to a nominal motion. This approach enables simulating the motion of large satellites. In particular, we exploit a Lagrangian matching relative to the nominal motion for a satellite (client) and a manipulator-equipped spacecraft (servicer), which are modeled as a rigid body and a multi-body system, respectively. Stability of the proposed method is also analyzed. The effectiveness of the method is demonstrated through experiments on the OOS-Sim facility for the capture of Envisat, a free-tumbling satellite and the largest space debris in Low-Earth-Orbit.

关键词： Dynamics space robotics and automation

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Slip-Based Autonomous ZUPT Through Gaussian Process to Improve Planetary Rover Localization

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IEEE robotics AND automation LETTERS 2021年第3期6卷 4782-4789页

作者： Kilic, Cagri Ohi, Nicholas Gu, Yu Gross, Jason West Virginia Univ Dept Mech & Aerosp Engn Morgantown WV 26506 USA

The zero-velocity update (ZUPT) algorithm provides valuable state information to maintain the inertial navigation system (INS) reliability when stationary conditions are satisfied. Employing ZUPT along with leveraging non-holonomic constraints can greatly benefit wheeled mobile robot dead-reckoning localization accuracy. However, determining how often they should be employed requires consideration to balance localization accuracy and traversal rate for planetary rovers. To address this, we investigate when to autonomously initiate stops to improve wheel-inertial odometry (WIO) localization performance with ZUPT. To do this, we propose a 3D dead-reckoning approach that predicts wheel slippage while the rover is in motion and forecasts the appropriate time to stop without changing any rover hardware or major rover operations. We validate with field tests that our approach is viable on different terrain types and achieves a 3D localization accuracy of similar to 97% over 650 m drives on rough terrain.

关键词： Location awareness Wheels space vehicles Extraterrestrial measurements Kernel Training Estimation space robotics and automation localization planetary rovers zero velocity update

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A Compliant Partitioned Shared Control Strategy for an Orbital Robot

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IEEE robotics AND automation LETTERS 2021年第4期6卷 7317-7324页

作者： Mishra, Hrishik Balachandran, Ribin De Stefano, Marco Ott, Christian German Aerosp Ctr DLR Inst Robot & Mechatron D-82234 Wessling Germany Tech Univ TU Wien Automat & Control Inst ACIN A-1040 Vienna Austria German Aerosp Ctr DLR Inst Robot & Mech D-82234 Wessling Germany

In this letter, a novel partitioned shared controller is proposed, which exploits a fully-actuated orbital robot to perform a primary end-effector task involving environmental interactions. This task is remotely performed using a bilateral teleoperation controller, while a secondary task is automatically controlled in situ for operational safety in a partitioned manner. In particular, the proposed method is derived as a modified 4-Channel teleoperation architecture. The orbital robot's momentum and shape (joints) dynamics are exploited to benefit the controller design. Asymptotic stability and finite-gain L-2-stability are proved in the absence and presence of external interactions, respectively. Furthermore, the proposed method is validated experimentally on a hardware-inthe-loop facility.

关键词： space robotics and automation human-robot collaboration compliance and impedance control

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

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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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