Abstract
Abstract Recent advances in robotics allow for collaboration between humans and machines in performing tasks at home or in industrial settings without harming the life of the user. While humans can easily adapt to each other and work in team, it is not as trivial for robots. In their case, interaction skills typically come at the cost of extensive programming and teaching. Besides, understanding the semantics of a task is necessary to work efficiently and react to changes in the task execution process. As a result, in order to achieve seamless collaboration, appropriate reasoning, learning skills and interaction capabilities are needed. For us humans, a cornerstone of our communication is language that we use to teach, coordinate and communicate. In this paper we thus propose a system allowing (i) to teach new action semantics based on the already available knowledge and (ii) to use natural language communication to resolve ambiguities that could arise while giving commands to the robot. Reasoning then allows new skills to be performed either autonomously or in collaboration with a human. Teaching occurs through a web application and motions are learned with physical demonstration of the robotic arm. We demonstrate the utility of our system in two scenarios and reflect upon the challenges that it introduces.
Highlights
Recent advances in robotics allow for collaboration between humans and machines in performing tasks at home or in industrial settings without harming the life of the user
In this paper we propose a system allowing (i) to teach new action semantics based on the already available knowledge and (ii) to use natural language communication to resolve ambiguities that could arise while giving commands to the robot
We focus on the transfer process from human to robot of the declarative knowledge. It is often expected of a robotic system to be able to verbalize this knowledge and we review in Section 2.2 the strategies around the symbol grounding problem or how to connect the information to the syntax of human language
Summary
Abstract: Recent advances in robotics allow for collaboration between humans and machines in performing tasks at home or in industrial settings without harming the life of the user. While humans can adapt to each other and work in team, it is not as trivial for robots In their case, interaction skills typically come at the cost of extensive programming and teaching. To successfully deploy a robot, it needs to be delivered with an intuitive interface for interaction and have access to learning capabilities to enable its coworkers to teach it the necessary operational skills. Current state of the art collaborative robots come with such systems (e.g., Franka Emika’s Panda [3], Rethink Robotics’ Sawyer [4]) They are delivered with a library of built-in apps that allow for the end-user to program various sequences of motions and grasping tasks, without having to go through a development phase, which considerably speeds up getting started with the robot.
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