Abstract
Abstract As a mobile robot navigates through an indoor environment, the condition of the floor is of low (or no) relevance to its decisions. In an outdoor environment, however, terrain characteristics play a major role on the robot’s motion. Without an adequate assessment of terrain conditions and irregularities, the robot will be prone to major failures, since the environment conditions may greatly vary. As such, it may assume any orientation about the three axes of its reference frame, which leads to a full six degrees of freedom configuration. The added three degrees of freedom have a major bearing on position and velocity estimation due to higher time complexity of classical techniques such as Kalman filters and particle filters. This article presents an algorithm for localization of mobile robots based on the complementary filtering technique to estimate the localization and orientation, through the fusion of data from IMU, GPS and compass. The main advantages are the low complexity of implementation and the high quality of the results for the case of navigation in outdoor environments (uneven terrain). The results obtained through this system are compared positively with those obtained using more complex and time consuming classic techniques.
Highlights
Recent advances in the computational foundations of robotics have led to the development of new algorithms and efficient methodologies for tackling several fundamental problems in robotics
Much of the effort that has been invested to increase the ability of mobile robots to make their own decisions has gone into tackling the core issues of mobility, namely localization and mapping, which are heavily dependent on data interpretation and fusion
This paper describes the use of a powerful, yet simple, precise and efficient technique known as CF10, 5 to tackle the localization problem for mobile robots navigating on uneven terrains in outdoor environments
Summary
Recent advances in the computational foundations of robotics have led to the development of new algorithms and efficient methodologies for tackling several fundamental problems in robotics. This paper describes the use of a powerful, yet simple, precise and efficient technique known as CF10, 5 to tackle the localization problem for mobile robots navigating on uneven terrains in outdoor environments. Different types of surface (e.g. gravel, sand, asphalt, grass) In such environments, the robot will no longer be moving on a flat horizontal surface, but its attitude will be constantly changing due to terrain irregularities, and its pose will have six degrees of freedom, which is represented by the →. It is shown the exact moment when the robot tranverses an obstacle, with a variation on its pitch angle. Several approaches have been reported in the literature, and the key ones will be presented and discussed
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