• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.38.3-38
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• 2001

In the planetary surface exploration , micro-rovers or nano-rovers are very attractive choices for a surface exploration system providing mobility functions and other features required in the surface probe missions at small mass and relatively small cost. This paper surveys and summarizes the requirements for Mars exploration rovers in micro or nano scale and outlines the control concepts for navigation including the obstacle/hazard avoidance and the path planning. In this context, autonomous reaction capabilities are the key elements to control design in conjunction with the remote control schemes to deal with the significant signal propagation delays. Other navigation and control aspects such as the instrument fine positioning and the flip-over of the rovers are also briefly introduced. The current technical limitations of the micro- and nano-rovers are summarized.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.243-253
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• 2019

First steps of Planetary exploration are usually conducted with the use of autonomous rovers. These rovers are capable of finding its own path and perform experiments about the planet's surface. This paper makes a proposal for a multi-agent system which effectively take the advantage of a blackboard system for share knowledge and effort of each agent. Agents use Reactive Model with the combination of Belief Desire Intension (BDI) Model and also use a Path Finding Algorithm for calculate shortest distance and a path for travel on the planet's surface. This approach can perform a surface exploration on a given terrain within a short period of time. Information which are gathered on the blackboard are used to make an output with detailed surface soil variance results. The developed Multi-Agent system performed well with different terrain sizes.

• Advances in aircraft and spacecraft science
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• v.1 no.4
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• pp.455-469
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• 2014

High-precision autonomous localization technique is essential for future Mars rovers. This paper addresses an innovative integrated localization algorithm using a multiple information fusion approach. Firstly, the output of IMU is employed to construct the two-dimensional (2-D) dynamics equation of Mars rover. Secondly, radio beacon measurement and terrain image matching are considered as external measurements and included into the navigation filter to correct the inertial basis and drift. Then, extended Kalman filtering (EKF) algorithm is designed to estimate the position state of Mars rovers and suppress the measurement noise. Finally, the localization algorithm proposed in this paper is validated by computer simulation with different parameter sets.