User imitation for multi-purpose robotics

拟议的研究计划的目标是开发技术的多用途代理，如机器人使用模仿技术的编程。模仿，一种通过演示进行编程的形式，特别适用于用户没有任何编程专业知识的情况：在“记录”模式下，用户只需远程控制机器人，同时记录行为。记录的日志以高级符号形式存储。在“播放”模式下，机器人使用记录的轨迹自主再现观察到的行为。 在我们的方法中特别创新的是，我们希望消除用户明确编码任务目标的需要，这在典型的基于案例的推理任务或依赖于强化学习的方法中是必需的。虽然这限制了机器人从错误中学习和调整的能力，但它也最大限度地减少了用户所需的输入量和编程技能，并且允许机器人真正多用途，并且可以轻松地重新编程以执行不同的任务。此外，建立在我们最初的成功与再现反应性行为在模拟环境（如RoboCup），我们建议扩大和推广我们的方法来模仿“有状态”，上下文感知行为在真实的生活中的机器人。这应该使该方法特别适合用于老年人或危险救援任务的辅助任务的机器人，其中环境复杂，任务的具体性质通常只能在“现场”确定，并且非专家将重新利用机器人执行新任务。

The objective of the proposed research program is to develop techniques for the programming of multi-purpose agents such as robots using imitation techniques. Imitation, a form of programming by demonstration, is particularly suitable when the user does not have any programming expertise: during "record" mode, the user would simply remote control the robot, while the behavior is being recorded. The recorded logs are stored in a high-level, symbolic form. During "play" mode, the robot uses the recorded traces to autonomously reproduce the behavior that was observed. What is particularly innovative in our approach is that we want to eliminate the need for the user to explicitly encode the goal of the task, as is required in typical case-based reasoning tasks or approaches relying on reinforcement learning. While this limits the ability of the robot to learn from its mistakes and adjust, it also minimizes the amount of input and programming skills required from the user and it allows for the robot to be truly multi-purpose and easily reprogrammable for a different task. Further, building on our initial success with reproducing reactive behavior in simulated environments (such as RoboCup), we propose to expand and generalize our approach to the imitation of "stateful", context-aware behavior in real life robots. This should make the approach particularly suitable for robots to be used in assistive tasks for the elderly or dangerous rescue missions, where the environment is complex, the specific nature of the tasks can often only be determined "on the field" and non-experts will be the ones re-purposing the robot for new tasks.