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Autonomous planetary rover navigation via active SLAM
Abstract
Purpose: This paper aims to introduce an efficient active-simultaneous localization and mapping (SLAM) approach for rover navigation, future planetary rover exploration mission requires the rover to automatically localize itself with high accuracy. Design/methodology/approach: A three-dimensional (3D) feature detection method is first proposed to extract salient features from the observed point cloud, after that, the salient features are employed as the candidate destinations for re-visiting under SLAM structure, followed by a path planning algorithm integrated with SLAM, wherein the path length and map utility are leveraged to reduce the growth rate of state estimation uncertainty. Findings: The proposed approach is able to extract distinguishable 3D landmarks for feature re-visiting, and can be naturally integrated with any SLAM algorithms in an efficient manner to improve the navigation accuracy. Originality/value: This paper proposes a novel active-SLAM structure for planetary rover exploration mission, the salient feature extraction method and active revisit patch planning method are validated to improve the accuracy of pose estimation.
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“(1) Planetary rover exploration is a global navigation satellite system-denied scenario [89].”
From Semantic Terrain Segmentation in the Navigation Vision of Planetary Rovers—A Systematic Literature Review (2022) · cites this paper as [89]
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References 33 · Cited by 11
Research works printed but not linked: 22
- 2014, Localization of planetary exploration rovers with orbital imaging: a survey of approaches
- 2017, Generic node removal for Factor-Graph SLAM, IEEE Transactions on Robotics, 30, 1371
- 2016, Multi-Objective design of optical systems for space situational awareness, Acta Astronautica, 128, 669, 10.1016/j.actaastro.2016.07.008 · DOI
- 2007, MonoSLAM: real-time single camera SLAM, IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 1052, 10.1109/TPAMI.2007.1049 · DOI · Paper page
- 2001, A computationally efficient solution to the simultaneous localisation and map building (SLAM) problem, Robotics & Automation IEEE Transactions On, 17, 229, 10.1109/70.938381 · DOI · Paper page
- 2002, Autonomous rover navigation on unknown terrains: functions and integration, The International Journal of Robotics Research, 21, 917, 10.1177/0278364902021010841 · DOI
- 2000, RoverBug: Long Range Navigation for Mars Rovers
- 2002, FastSLAM: a factored solution to the simultaneous localization and mapping problem, Aaai/iaai, 593
- 2003, Rover navigation using stereo ego-motion, Robotics and Autonomous Systems, 43, 215, 10.1016/S0921-8890(03)00004-6 · DOI · Paper page
- 2009, Experimental results for over-the-Horizon Planetary exploration using a LIDAR sensor, 65
- 1996, Fisher information and stochastic complexity, IEEE Transactions on Information Theory, 42, 40, 10.1109/18.481776 · DOI · Paper page
- 2017, An approach to build simplified semi-autonomous mars rover, 3502
- 2015, Next-generation rover GNC architectures
- 2017, Simple texture descriptors for classifying monochrome planetary rover terrains, 5495
- 2005, Probabilistic Robotics
- 2013, A New Method for Real-Time High-Precision Planetary Rover Localization and Topographic Mapping
- 2017, Adaptive and intelligent navigation of autonomous planetary rovers – a survey, NASA ESA Conference on Adaptive Hardware and Systems, 237
- 2014, Seeker – autonomous long‐range rover navigation for remote exploration, Journal of Field Robotics, 31, 940, 10.1002/rob.21528 · DOI
- 2015, An overview to visual odometry and visual SLAM: applications to mobile robotics, Intelligent Industrial Systems, 1, 289, 10.1007/s40903-015-0032-7 · DOI
- 2017, Database construction for vision aided navigation in planetary landing, Acta Astronautica, 140
- 1994, Iterative point matching for registration of free-form curves and surfaces, International Journal of Computer Vision, 13, 119, 10.1007/BF01427149 · DOI
- 2017, A survey of visual SLAM based on deep learning, Robotics, 39, 889
Metadata
- Authors
- Li, G., Geng, Y., & Zhang, W.
- Affiliations
- Harbin Institute of Technology (CN)
- Venue
- Aircraft Engineering and Aerospace Technology
- Publisher
- Emerald
- Published
- 2018-01-07
- Volume
- 91
- Issue
- 1
- Pages
- 60-68
- ISSN
- 0002-2667 (ISSN-L)
- 1748-8842
- OpenAlex
- W2901333117
- Cited by
- 11
- References
- 33
- Citations by year
- 2025: 3 · 2023: 1 · 2022: 3 · 2021: 3 · 2019: 1
- FWCI
- 0.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Aircraft Engineering and Aerospace Technology (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Path Planning Algorithms
- Keywords
- active SLAM, SLAM, point clouds, salient feature extraction, path planning, pose estimation, state estimation uncertainty, autonomous navigation
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- The paper
- Li, G., Geng, Y., & Zhang, W. (2018). Autonomous planetary rover navigation via active SLAM. Aircraft Engineering and Aerospace Technology. https://doi.org/10.1108/aeat-12-2016-0239
