Robust Path Planning for Space Exploration Rovers

Metadata Updated: May 2, 2019

Motion planning considers the problem of moving a system from a starting position to a desired goal position. This problem has been shown to be a computationally challenging task. This mainly arises due to complexity of the system being controlled and environmental factors that occur in the real world, such as sensor noise and imperfect actuation. The system being controlled might also have many degrees of freedom, allowing more complex tasks such as manipulation of the environment. A motion planner that can handle these type of disturbances and capabilities is ideal to produce robust paths that robotic systems can follow.

The proposed work will attempt to address these issues by building off of state-of-the-art research in asymptotically optimal sampling-based motion planning. This process will involve developing an algorithm that can efficiently solve the motion planning problem for system that have dynamic constraints on their movement, e.g. car-like vehicles. By developing an algorithm that can provide optimality for dynamical systems, many other applications may be branched off of it.

The first application to explore in this direction is planning under uncertainty. The uncertainty in environment and actuation is observed in the real world whenever we use a robotic system. This uncertainty is magnified when performing extra-terrestrial rover missions from ground stations here. It would be beneficial to have an autonomous planner be able to handle these disturbances, allowing ground crew to focus on more important tasks, such as waypoint selection.

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Public: This dataset is intended for public access and use. License: U.S. Government Work

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Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019
Publisher Space Technology Mission Directorate
Unique Identifier TECHPORT_91560
Maintainer Email
Public Access Level public
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Datagov Dedupe Retained 20190501230127
Harvest Object Id fe3a4d63-2b12-43f7-9e26-a2d2e8e3f7c6
Harvest Source Id 39e4ad2a-47ca-4507-8258-852babd0fd99
Harvest Source Title NASA Data.json
Data First Published 2017-08-01
Homepage URL
Data Last Modified 2018-07-19
Program Code 026:027
Source Datajson Identifier True
Source Hash 53d2cf6094d20b3a9c4387da06c24157dba8a91f
Source Schema Version 1.1

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