Harmonious Robot Navigation Strategies for Pedestrians in Dynamic Environment

Author(s):  
Shintaro NAKAOAKA ◽  
Ayanori YOROZU ◽  
Masaki TAKAHASHI
Robotica ◽  
2009 ◽  
Vol 28 (3) ◽  
pp. 465-475 ◽  
Author(s):  
Edith Heußlein ◽  
Blair W. Patullo ◽  
David L. Macmillan

SUMMARYBiomimetic applications play an important role in informing the field of robotics. One aspect is navigation – a skill automobile robots require to perform useful tasks. A sub-area of this is search strategies, e.g. for search and rescue, demining, exploring surfaces of other planets or as a default strategy when other navigation mechanisms fail. Despite that, only a few approaches have been made to transfer biological knowledge of search mechanisms on surfaces along the ground into biomimetic applications. To provide insight for robot navigation strategies, this study describes the paths a crayfish used to explore terrain. We tracked movement when different sets of sensory input were available. We then tested this algorithm with a computer model crayfish and concluded that the movement of C. destructor has a specialised walking strategy that could provide a suitable baseline algorithm for autonomous mobile robots during navigation.


Robotica ◽  
2005 ◽  
Vol 23 (6) ◽  
pp. 709-720 ◽  
Author(s):  
F. Belkhouche ◽  
B. Belkhouche

This paper deals with a method for robot navigation towards a moving goal. The goal maneuvers are not a priori known to the robot. Our method is based on the use of the kinematics equations of the robot and the goal combined with geometrical rules. First a kinematics model for the tracking problem is derived and two strategies are suggested for robot navigation, namely the velocity pursuit guidance law and the deviated pursuit guidance law. It turns out that in both cases, the robot's angular velocity is equal to the line of sight angle rate. Important properties of the navigation strategies are discussed and proven. In the presence of obstacles, two navigation modes are used: the tracking mode, which has a global aspect and the obstacle avoidance mode, which has a local aspect. In the obstacle avoidance mode, a polar diagram combining information about obstacles and directions corresponding to the pursuit is constructed. An extensive simulation study is carried out, where the efficiency of both strategies is illustrated for different scenarios.


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