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

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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Virtual IR Sensing for Planetary Rovers: Improved Terrain Classification and Thermal Inertia Estimation

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IEEE robotics AND automation LETTERS 2020年第4期5卷 6302-6309页

作者： Iwashita, Yumi Nakashima, Kazuto Gatto, Joseph Higa, Shoya Stoica, Adrian Khoo, Norris Kurazume, Ryo CALTECH Jet Prop Lab Pasadena CA 91109 USA Kyushu Univ Fukuoka 8190395 Japan Columbia Univ New York NY 10027 USA Univ Southern Calif Los Angeles CA 90007 USA

Terrain classification is critically important for Mars rovers, which rely on it for planning and autonomous navigation. On-board terrain classification using visual information has limitations, and is sensitive to illumination conditions. Classification can be improved if one fuses visual imagery with additional infrared (IR) imagery of the scene, yet unfortunately there are no IR image sensors on the current Mars rovers. A virtual IR sensor, estimating IR from RGB imagery using deep learning, was proposed in the context of a MU-Net architecture. However, virtual IR estimation was limited by the fact that slope angle variations induce temperature differences within the same terrain. This paper removes this limitation, giving good IR estimates and as a consequence improving terrain classification by including the additional angle from the surface normal to the Sun and the measurement of solar radiation. The estimates are also useful when estimating thermal inertia, which can enhance slip prediction and small rock density estimation. Our approach is demonstrated in two applications. We collected a new data set to verify the effectiveness of the proposed approach and show its benefit by applying to the two applications.

关键词： space robotics and automation multi-modal perception

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Cat-Like Jumping and Landing of Legged Robots in Low Gravity Using Deep Reinforcement Learning

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IEEE TRANSACTIONS ON robotics 2022年第1期38卷 317-328页

作者： Rudin, Nikita Kolvenbach, Hendrik Tsounis, Vassilios Hutter, Marco Swiss Fed Inst Technol Robot Syst Lab CH-8092 Zurich Switzerland

In this article, we show that learned policies can be applied to solve legged locomotion control tasks with extensive flight phases, such as those encountered in space exploration. Using an off-the-shelf deep reinforcement learning algorithm, we train a neural network to control a jumping quadruped robot while solely using its limbs for attitude control. We present tasks of increasing complexity leading to a combination of 3-D (re)orientation and landing locomotion behaviors of a quadruped robot traversing simulated low-gravity celestial bodies. We show that our approach easily generalizes across these tasks and successfully trains policies for each case. Using sim-to-real transfer, we deploy trained policies in the real world on the spaceBok robot placed on an experimental testbed designed for 2-D microgravity experiments. The experimental results demonstrate that repetitive controlled jumping and landing with natural agility is possible.

关键词： Robots Legged locomotion Task analysis Actuators Gravity Training Kinematics Deep learning in robotics and automation legged robots space robotics and automation

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Active Traversability Learning via Risk-Aware Information Gathering for Planetary Exploration Rovers

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IEEE robotics AND automation LETTERS 2022年第4期7卷 11855-11862页

作者： Endo, Masafumi Ishigami, Genya Keio Univ Dept Mech Engn Space Robot Grp Yokohama Kanagawa 2238522 Japan

Traversability prediction enables safe and efficient autonomous rover operation on deformable planetary surfaces. Revealing spatial distribution from terrain geometry to rover slip behavior is key to assessing prospective traversability, but is hindered by insufficient in situ measurements on hazardous states due to conservative rover traverses. To achieve a more accurate prediction, this letter proposes a framework that actively learns latent traversability by exploring informative terrain under the constraints of stochastic rover slip. With a Gaussian process (GP) modeling the spatial distribution, we devise an iterative two-stage framework that gradually refines the model estimation, combining risk-aware informative path planning and GP updates by taking in situ measurements. The path planning stage employs our designed sampling-based algorithm to generate informative trajectories with fault-tolerant risk inference, while the GP is cautiously updated with traverse data to avoid rover immobilization. Chance constraint formulation is exploited in the framework to infer the stochastic reachability of informative regions. Through GP estimates reducing uncertainty, the algorithm incrementally reaches informative yet hazardous states along feasible trajectories. Simulation studies in rough terrain environments demonstrate that the proposed framework gathers informative traverse data while averting rover stuck situations to estimate the latent traversability model.

关键词： Field robots motion and path planning probabilistic inference space robotics and automation

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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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Design, Execution, and Postmortem Analysis of Prolonged Autonomous Robot Operations

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IEEE robotics AND automation LETTERS 2018年第2期3卷 1056-1063页

作者： Brunner, Sebastian G. Lehner, Peter Schuster, Martin J. Riedel, Sebastian Belder, Rico Leidner, Daniel Wedler, Armin Beetz, Michael Stulp, Freek German Aerosp Ctr DLR RMC D-82234 Wessling Germany Univ Bremen IAI D-85748 Bremen Germany

In the context of space missions and terrestrial applications, both mission goals and task implementations for autonomous robots are becoming increasingly complex. Thus, the challenge of monitoring the achievement of task objectives and checking the correctness of their implementation is becoming more and more difficult. To tackle these problems, we propose an unified architecture that supports different stakeholders during the different phases of the deployment: 1) the design phase;2) the runtime phase;and 3) the postmortem analysis phase. Furthermore, we implement this architecture by enhancing our task programming framework RMC advanced flow control with powerful logging, debugging, and profiling capabilities. We demonstrate the efficiency of our approach in the context of the ROBEX mission, during which the DLR Lightweight Rover Unit autonomously deployed several seismometers in an unknown rough terrain on Mt. Etna, Sicily. The analysis results for a state machine consisting of more than 1500 states and more than 1900 transitions are presented. Finally, we give a comparison between our framework and related software tools.

关键词： Software middleware and programming environments field robots space robotics and automation autonomous agents mobile manipulation

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Coordinated Control of spacecraft's Attitude and End-Effector for space Robots

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IEEE robotics AND automation LETTERS 2019年第2期4卷 2108-2115页

作者： Giordano, Alessandro Massimo Ott, Christian Albu-Schaeffer, Alin Univ Munich Dept Informat D-85748 Garching Germany German Aerosp Ctr DLR Inst Robot & Mechatron D-82234 Wessling Germany

This letter addresses the coordinated control of the spacecraft's attitude and the end-effector pose of a manipulator-equipped space robot. A controller is proposed to simultaneously regulate the spacecraft's attitude, the global center-of-mass, and the end-effector pose. The control is based on a triangular actuation decomposition that decouples the end-effector task from the spacecraft's force actuator, increasing fuel efficiency. The strategy is validated in hardware using a robotic motion simulator composed of a seven degrees-of-freedom (DOF) arm mounted on a six DOF base. The tradeoff between control requirements and fuel consumption is discussed.

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

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Redundancy parameterization and inverse kinematics of 7-DOF revolute manipulators

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MECHANISM AND MACHINE THEORY 2024年 204卷

作者： Elias, Alexander J. Wen, John T. Rensselaer Polytech Inst Dept Elect Comp & Syst Engn 110 8th St Troy NY 12180 USA

Seven-degree-of-freedom (DOF) robot arms have one redundant DOF for obstacle and singularity avoidance which must be parameterized to fully specify the joint angles for a given end effector pose. Commonly used 7-DOF revolute (7R) industrial manipulators from ABB, Motoman, and KUKA and space manipulators like SSRMS or FREND are conventionally parameterized by the shoulder-elbow-wrist (SEW) angle for path planning and teleoperation. We introduce the general SEW angle which generalizes the conventional SEW angle with an arbitrary reference direction function. Redundancy parameterizations such as the conventional SEW angle encounter an algorithmic singularity along a line in the workspace. We introduce a reference direction function choice called the stereographic SEW angle which has a singularity only along a half-line which can be out of reach, enlarging the usable workspace. We prove all parameterizations have an algorithmic singularity. Finally, using the general SEW angle and subproblem decomposition, we provide efficient singularity-robust inverse kinematics solutions which are often closed-form but may involve a 1D or 2D search. Search-based solutions may be converted to finding polynomial roots. Examples are available in a publicly accessible repository.

关键词： Kinematics Redundant robots Industrial robots space robotics and automation Telerobotics and teleoperation Humanoid robot systems

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Revisiting Scaling Laws for Robotic Mobility in Granular Media

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IEEE robotics AND automation LETTERS 2020年第2期5卷 1319-1325页

作者： Thoesen, Andrew McBryan, Teresa Green, Marko Mick, Darwin Martia, Justin Marvi, Hamid Arizona State Univ Sch Engn Matter Transport & Energy Ira A Fulton Sch Engn Tempe AZ 85287 USA

The development, building, and testing of robotic vehicles for applications in deformable media can be costly. Typical approaches rely on full-sized builds empirically evaluating performance metrics such as drawbar pull and slip. Recently developed granular scaling laws offer a new opportunity for terramechanics as a field. Using non-dimensional analysis on the wheel characteristics and treating the terrain as a deformable continuum, the performance of a larger, more massive wheel may be predicted from a smaller one. This allows for new wheel design approaches. However, robot-soil interaction and specific characteristics of the soil or robot dynamics may create discrepancies in prediction. In particular, we find that for a lightweight rover (2;5;kg), the scaling laws significantly overpredicted mechanical power requirements. To further explore the limitations of the current granular scaling laws, a pair of differently sized grousered wheels were tested at three masses and a pair of differently sized sandpaper wheels were tested at two masses across five speeds. Analysis indicates similar error for both designs, a mass dependency for all five pairs that explains the laws;overprediction, and a speed dependency for both of the heaviest sets. The findings create insights for using the laws with lightweight robots in granular media and generalizing granular scaling laws.

关键词： Field robots mining robotics space robotics and automation wheeled robots

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Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras

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IEEE robotics AND automation LETTERS 2020年第2期5卷 580-587页

作者： Giubilato, Riccardo Vayugundla, Mallikarjuna Schuster, Martin J. Stuerzl, Wolfgang Wedler, Armin Triebel, Rudolph Debei, Stefano Univ Padua CISAS Giuseppe Colombo Via Venezia 15 I-35131 Padua Italy German Aerosp Ctr DLR Inst Robot & Mechatron Munchener Str 20 D-82234 Wessling Germany

To enable long term exploration of extreme environments such as planetary surfaces, heterogeneous robotic teams need the ability to localize themselves on previously built maps. While the Localization and Mapping problem for single sessions can be efficiently solved with many state of the art solutions, place recognition in natural environments still poses great challenges for the perception system of a robotic agent. In this paper we propose a relocalization pipeline which exploits both 3D and visual information from stereo cameras to detect matches across local point clouds of multiple SLAM sessions. Our solution is based on a Bag of Binary Words scheme where binarized SHOT descriptors are enriched with visual cues to recall in a fast and efficient way previously visited places. The proposed relocalization scheme is validated on challenging datasets captured using a planetary rover prototype on Mount Etna, designated as a Moon analogue environment.

关键词： Localization space robotics and automation mapping

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