Abstract
Paths will be re-planed timely according the change of obstacles and target position for Human Following Robots (HFRs) so that they can run safely and rapidly. Traditional path planning algorithms are generally focused on how to avoid obstacles or connect with the new target position effectively, however there are rarely studies on the elimination of robot heading fluctuation which is caused by path re-planning. Concerning this issue, we introduce a novel dynamic path re-planning algorithm AT* which is based on A* and walkable area thinning. When robots heading difference value between the current and the last moment which is derived from A* exceeds the threshold, AT* will search for path connection points by walkable area thinning, and then a new path going through optimal connection point and meeting heading constraints will be planned. Thinning algorithm is improved in order to make the passable skeleton can connect path origin and the end. Results from simulation experiments show that AT* algorithm keeps heading stability as a priority at path re-planning and the robot motion stability can be improved effectively.
Highlights
With the development of modern robot technology, more and more robots are integrated into people’s daily life and changing our lifestyle dramatically
Most traditional path planning algorithms are generally focused on how to avoid obstacles or connect with the new target position, but work do not consider the elimination of robot heading fluctuation which is caused by path re-planning
When robots heading difference value between the current and last moment which is derived from the path planned by A∗ exceeds the threshold, AT∗ will search for connection points by walkable area thinning, and a new path going through optimal connection point and meeting heading constraints will be re-planned
Summary
With the development of modern robot technology, more and more robots are integrated into people’s daily life and changing our lifestyle dramatically. Most traditional path planning algorithms are generally focused on how to avoid obstacles or connect with the new target position, but work do not consider the elimination of robot heading fluctuation which is caused by path re-planning. When robots heading difference value between the current and last moment which is derived from the path planned by A∗ exceeds a threshold, AT∗ will search for connection points by walkable area thinning, and FIGURE 5. In order to avoid local heading optimal such as caused by VFH, we use a global passable skeleton map which is derived from passable area thinning based on the popular Zhang-Suen algorithm to select optimal connecting point [21]–[23]. A new route from r3 to the path start point and end point can be re-planned by A∗ as showed in Fig. 12(b) and this path will satisfy the heading constraint
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