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The lancelet is an important animal in evolutionary studies. Artificial proliferation is necessary to secure individuals for experiments. However, the number of individuals and their habitats are decreasing remarkably in the Ariake Sea. Despite the transplantation of frys, the number of adults has not increased. In addition, basic data such as water parameters and bottom conditions in the habit have...
This paper deals with a collision avoidance problem for path-following of multiple holonomic robots. The path-following aims to move the robots along reference paths with assigned velocities. When there are geometric errors between the robots' positions and the reference paths or when the differences between their velocities and assigned velocities are not zero, we expect to reduce these errors. Unfortunately,...
In this paper, we discuss the leader-following formation navigation (LFFN), which is one of the most important issues in formation control. In this formation, one leader is controlled by a human operator, while multiple followers pass along the leader's trajectory in the same motion to the leader. The collision avoidance problem in the LFFN has been discussed in a previous work. However, the problem...
Adaptiveness is one of the target functions of research on autonomous robotic systems. However, the adaptiveness realized in the robotic research so far is quite limited and specific to sample problems and systems configurations. On the other hand, all the animals from primitive ones to insects or mammals have commonly the adaptiveness to behave in an unexpected environment. Such adaptive behaviors...
This paper addresses online modification of reference trajectories for multiple robots with collision avoidance. A smooth mapping dependent on the distances between robots has been proposed to coordinate collision-free motion from given reference trajectories. The trajectories generated by the mapping allow the robots to avoid collisions with each other and are smooth enough to be tracked by the robots...
The present paper proposes an objective-based reinforcement learning system for multiple autonomous mobile robots to acquire cooperative behavior. The proposed system employs profit sharing (PS) as a learning method. A major characteristic of the system is using two kinds of PS tables. One is to learn cooperative behavior using information on other agents' positions and the other is to learn how to...
This paper addresses online modification of reference trajectories for multiple robots with collision avoidance. First, a smooth mapping dependent on the relative distances between the robots is proposed to coordinate collision-free motion from given reference trajectories. The trajectories modified by the mapping make the robots avoid collisions with each other, and are smooth enough to be tracked...
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