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As Human-Robot Interaction becomes closer, it is necessary to seek human safety so that the robot does not harm the human when the human ventures into the robot's workspace. Therefore, we propose a reactive strategy for human safety called Asymmetric Velocity Moderation. Our proposed method restricts the velocity of the end-effector according to the distance between human and robot. Moreover, our...
Reinforcement learning (RL) applications in robotics are of great interest because of their wide applicability, however many RL applications suffer from large learning costs. We study a new learning-walking scheme where a humanoid robot is embedded with a primitive balancing controller for safety. In this paper, we investigate some RL methods for the walking task. The system has two modes: double...
This paper introduces a software library of reinforcement learning (RL) methods, named SkyAI. SkyAI is a highly modularized RL library for real/simulated robots to learn behaviors. Our ultimate goal is to develop an artificial intelligence (AI) program with which the robots can learn to behave as their users' wish. In this paper, we describe the concepts, the requirements, and the current implementation...
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