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An autonomous sensor-based path-planner for planetary microrovers
Abstract
With the success of Mars Pathfinder's Sojourner rover, a new era of planetary exploration has opened, with demand for highly capable mobile robots. These robots must be able to traverse long distances over rough, unknown terrain autonomously, under severe resource constraints. This paper reviews issues which are critical for successful autonomous navigation of planetary rovers. We report on the "Wedgebug" algorithm for planetary rover navigation. This algorithm is complete, correct, requires minimal memory for storage of its world model, and uses only on-board sensors, which are guided by the algorithm to efficiently sense only the data needed for motion planning. The implementation of a version of Wedgebug on the Rocky7 Mars rover prototype at the Jet Propulsion Laboratory is described, and experimental results from operation in simulated martian terrain are presented.
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Laubach et al. developed a sensor-based wedge bug reactive algorithm and validated it experimentally on Rocky 7.
“Laubach et al. developed a sensorbased wedge bug reactive algorithm and validated it experimentally on Rocky 7. 228”
From Energy system and resource utilization in space: A state-of-the-art review (2024) · cites this paper as [228]
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References 12 · Cited by 71
Research works printed but not linked: 1
- 1995, MGS Investigation Description and Science Requirement Document
Metadata
- Authors
- Laubach, S. L., & Burdick, J. W.
- Affiliations
- Jet Propulsion Laboratory (US)
- California Institute of Technology (US)
- ORCID
- Burdick, J.W.
- Venue
- Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)
- Publisher
- IEEE
- Published
- 2003-01-20
- Volume
- 1
- Pages
- 347-354
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W1653547394
- Cited by
- 71
- References
- 12
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 3 · 2021: 1 · 2019: 3 · 2017: 2 · 2015: 3 · 2014: 1 · 2013: 2 · 2012: 3
- FWCI
- 5.91
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (publishedVersion)
- Funders
- National Aeronautics and Space Administration
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Path Planning Algorithms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Keywords
- autonomous navigation, path planning, world models, resource-constrained robots, mobile robots
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