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For a robot to move autonomously in an unknown dynamic environment, a real-time motion planning is necessary. When the motions of obstacles are unknown, motion planning is usually performed by virtually expanding the area obstacles occupy. However, there are many cases in which the adequate solution trajectory cannot be obtained due to inadequate expansion. Another approach would be to determine candidates of the safe trajectory from the layout of obstacles as a generalized Voronoi diagram and then randomly search for an appropriate trajectory. However, this requires many calculations. It may be sufficient if a local generalized Voronoi diagram is available for limiting the sampling area. Based on this idea, this paper proposes a Voronoi-based StRRT composed of an StRRT subjected to biasing extraction of sample points toward the border of a generalized Voronoi diagram and show the possibilities of this method to plan safe trajectories.

It is expected that more and more robots will be introduced into public societies and homes. The problem in such a case will be the smooth mobility of each robot. Collision avoidance between robots or between a robot and other obstacles including human beings is important as well as reaching its target point in order to carry out its task. Human beings often give way to each other to cope with this collision avoidance problem in a decentralized manner in which they plan and move individually without mutually exchanging information. This paper demonstrates that the robot can produce giving way to each other behavior similar to human beings based on a decentralized approach. Spatiotemporal RRT, which is an extended version of Rapidly exploring Random Trees (RRT) that is a random sampling method for searching a large working space effectively, is used in order to produce this behavior. This paper also presents three typical types of environments that require giving way to each other and explains the result of numerical simulation with the proposed method.

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For a robot to move autonomously in an unknown in the workspace. When utilizing this technique in real-time dynamic environment a real-time motion generation is necessary. motion planning, the efficiency of searching for the path can Especially, safety motion generations are impoant. There are a be further improved by partially reusing or refining an existing lot of methods for making safe motion. For example, it is popular to check only around the robot with additional sensors and avoid tree. obstacles detected by the sensors though the coordination problem A common approach to handle moving obstacles utilizes a between global trajectory making and local obstacle avoidance should configurationtime space which consists in adding the time be occrued in this way. It is also popular to estimate the size dimension to the robot's configuration space [7]. Although this of obstacles to be large though adequate width of the dilatation method has usually been applied to motion planning in a is different by environment. Another approach would be to deter-ald to