The robot mechanisms that were previously researched had only been conducted for the purpose of overcoming the obstacles stably at low speed driving and enhancing the stability against high speed circuitous driving, and yet, the mechanism satisfying two purposes. However, in order to stably drive with high speed on rough terrain, there is a need for satisfying both of these purposes, as well as testing the efficiency of the mechanisms at high speed driving. There, this paper simulated some of the passive mechanisms and focused on checking the performances of passive mechanisms through simulations and analyzing each mechanism on the basis of an evaluation index. The simulation was conducted by Adams (The Multi-body Dynamics Simulation Solution) and used various types of passive mechanisms which were introduced in the robotics field. As a result, the study confirmed that passive mechanisms have a number of situations that affect the driving stability on each direction of roll and pitch. Further study is needed about active mechanism.
Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot. 효율적인 주행 방법이 제시되었다 [6][7][8][9][10][11] . 따라서 영상 센서 와 레이저 거리센서로부터 얻어지는 데이터는 로봇이 직
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