Author Description

<p>In this book, we have set up a unified analytical framework for various human-robot systems, which involve peer-peer interactions (either space-sharing or time-sharing) or hierarchical interactions. A methodology in designing the robot behavior through control, planning, decision and learning is proposed. In particular, the following topics are discussed in-depth: <i>safety </i>during human-robot interactions, <i>efficiency</i> in real-time robot motion planning<i>, imitation</i> of human behaviors from demonstration, <i>dexterity</i> of robots to adapt to different environments and tasks, <i>cooperation</i> among robots and humans with conflict resolution. These methods are applied in various scenarios, such as human-robot collaborative assembly, robot skill learning from human demonstration, interaction between autonomous and human-driven vehicles, etc.</p><p></p><p>Key Features: </p><p></p><ul> <p><li>Proposes a unified framework to model and analyze human-robot interactions under different modes of interactions.</li> <p><li>Systematically discusses the control, decision and learning algorithms to enable robots to interact safely with humans in a variety of applications.</li> <p><li>Presents numerous experimental studies with both industrial collaborative robot arms and autonomous vehicles.</li> </ul>