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相关论文: LunarNav: Crater-based Localization for Long-range…

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Real-time analysis of Martian craters is crucial for mission-critical operations, including safe landings and geological exploration. This work leverages the latest breakthroughs for on-the-edge crater detection aboard spacecraft. We…

Planetary exploration using aerial assets has the potential for unprecedented scientific discoveries on Mars. While NASA's Mars helicopter Ingenuity proved flight in Martian atmosphere is possible, future Mars rotorcraft will require…

计算机视觉与模式识别 · 计算机科学 2026-04-24 Dario Pisanti , Robert Hewitt , Roland Brockers , Georgios Georgakis

Planetary exploration robots must navigate uneven terrain while building reliable maps for space missions. However, most existing methods incorporate traversability constraints but may not handle high uncertainty in elevation estimates near…

机器人学 · 计算机科学 2025-11-18 Miryeong Park , Dongjin Cho , Sanghyun Kim , Younggun Cho

A stable, reliable, and controllable orbit lock system is crucial to an electron (or ion) accelerator because the beam orbit and beam energy instability strongly affect the quality of the beam delivered to experimental halls. Currently,…

机器学习 · 计算机科学 2024-01-30 Zhiyuan Chen , Wei Lu , Radhika Bhong , Yimin Hu , Brian Freeman , Adam Carpenter

Recently, there has been a growing interest in the use of a SmallSat platform for the future Lunar Navigation Satellite System (LNSS) to allow for cost-effectiveness and rapid deployment. However, many design choices are yet to be finalized…

机器人学 · 计算机科学 2022-01-04 Sriramya Bhamidipati , Tara Mina , Grace Gao

In this work we show that modern data-driven machine learning techniques can be successfully applied on lunar surface remote sensing data to learn, in an unsupervised way, sufficiently good representations of the data distribution to enable…

天体物理仪器与方法 · 物理学 2020-01-15 Adam Lesnikowski , Valentin T. Bickel , Daniel Angerhausen

(abridged) The technique of gravitational microlensing is currently unique in its ability to provide a sample of terrestrial exoplanets around both Galactic disk and bulge stars, allowing to measure their abundance and determine their…

The Mars Perseverance rover applies computer vision for navigation and hazard avoidance. The challenge to do onboard object recognition highlights the need for low-power, customized training, often including low-contrast backgrounds. We…

计算机视觉与模式识别 · 计算机科学 2021-04-12 David Noever , Samantha E. Miller Noever

Enabling fully autonomous robots capable of navigating and exploring large-scale, unknown and complex environments has been at the core of robotics research for several decades. A key requirement in autonomous exploration is building…

机器人学 · 计算机科学 2021-02-11 Kamak Ebadi , Matteo Palieri , Sally Wood , Curtis Padgett , Ali-akbar Agha-mohammadi

Tactful coordination on earth between hundreds of operators from diverse disciplines and backgrounds is needed to ensure that Martian rovers have a high likelihood of achieving their science goals while enduring the harsh environment of the…

Two radio-science instruments have included into the Luna-Glob and Luna-Resource projects in the frame of Russian Luna exploration program: the lander's radio beacon and the orbiter's receiver. Three types of experiments are planned:…

天体物理仪器与方法 · 物理学 2015-12-16 V. D. Gromov , A. S. Kosov

The resurgence of lunar operations requires advancements in cislunar navigation and Space Situational Awareness (SSA). Challenges associated to these tasks have created an interest in autonomous planning, navigation, and tracking…

机器人学 · 计算机科学 2024-09-02 Trevor N. Wolf , Brandon A. Jones

One objective of Artemis science is to determine the impact human activities have on the lunar environment, which might compromise science objectives and measurements. We perform a preliminary analysis of the contamination associated with…

空间物理 · 物理学 2026-02-18 Stefano Boccelli , William M. Farrell , Prabal Saxena , Orenthal J. Tucker

We present ARTPS (Autonomous Rover Target Prioritization System), a novel hybrid AI system that combines depth estimation, anomaly detection, and learnable curiosity scoring for autonomous exploration of planetary surfaces. Our approach…

计算机视觉与模式识别 · 计算机科学 2025-09-03 Poyraz Baydemir

Traversability assessment of deformable terrain is vital for safe rover navigation on planetary surfaces. Machine learning (ML) is a powerful tool for traversability prediction but faces predictive uncertainty. This uncertainty leads to…

机器人学 · 计算机科学 2024-09-04 Masafumi Endo , Tatsunori Taniai , Genya Ishigami

Existing navigation systems mostly consider "success" when the robot reaches within 1m radius to a goal. This precision is insufficient for emerging applications where the robot needs to be positioned precisely relative to an object for…

机器人学 · 计算机科学 2024-12-30 Xiangyun Meng , Xuning Yang , Sanghun Jung , Fabio Ramos , Srid Sadhan Jujjavarapu , Sanjoy Paul , Dieter Fox

This paper presents a navigation strategy to fly to the Moon along a Weak Stability Boundary transfer trajectory. A particular strategy is devised to ensure capture into an uncontrolled relatively stable orbit at the Moon. Both uncertainty…

最优化与控制 · 数学 2015-06-05 Massimo Vetrisano , Willem van der Weg , Massimiliano Vasile

As humanity prepares for new missions to the Moon and Mars, astronauts will need to operate with greater autonomy, given the communication delays that make real-time support from Earth difficult. For instance, messages between Mars and…

Autonomous exploration of unknown space is an essential component for the deployment of mobile robots in the real world. Safe navigation is crucial for all robotics applications and requires accurate and consistent maps of the robot's…

机器人学 · 计算机科学 2026-01-13 Sotiris Papatheodorou , Simon Boche , Sebastián Barbas Laina , Stefan Leutenegger

The ability to traverse an unknown environment is crucial for autonomous robot operations. However, due to the limited sensing capabilities and system constraints, approaching this problem with a single robot agent can be slow, costly, and…

机器人学 · 计算机科学 2024-06-13 Friedrich M. Rockenbauer , Jaeyoung Lim , Marcus G. Müller , Roland Siegwart , Lukas Schmid