A Framework to Describe, Analyze and Generate Interactive Motor Behaviors

Abstract

While motor interaction between a robot and a human, or between humans, has important implications for society as well as promising applications, little research has been devoted to its investigation. In particular, it is important to understand the different ways two agents can interact and generate suitable interactive behaviors. Towards this end, this paper introduces a framework for the description and implementation of interactive behaviors of two agents performing a joint motor task. A taxonomy of interactive behaviors is introduced, which can classify tasks and cost functions that represent the way each agent interacts. The role of an agent interacting during a motor task can be directly explained from the cost function this agent is minimizing and the task constraints. The novel framework is used to interpret and classify previous works on human-robot motor interaction. Its implementation power is demonstrated by simulating representative interactions of two humans. It also enables us to interpret and explain the role distribution and switching between roles when performing joint motor tasks.

Continuous Role Adaptation for Human–Robot Shared Control

“…In particular, the human and the robot are involved in a common game and have individual objectives (described by individual cost functions). In game theory, different types of multi-agent behaviors, such as cooperation and competition, have been defined and analyzed [26]. We follow the characterization of multi-agent behaviors in terms of the relationship between the cost functions of individual agents [29], [30].…”

“…In [25], role adaptation was achieved by adaptive attitude design depending on the disagreement level and the environmental situation, and the possibility of using game theory for the modeling of attitude negotiation between two partners was suggested. As discussed in [26], game theory provides useful tools to analyze complex interactive behaviors involving multiple agents.…”

Challenges for the understanding of the dynamics of social coordination

“…Agency, motor resonance, out of body experience extended to another’s body (Farrer and Frith, 2002; Keysers and Gazzola, 2009; Blanke, 2012; Tajadura-Jiménez et al, 2012), all appear to rely on multisensory integration phenomena. Another promising challenge is to close the gap between the present framework and a game theoretic framework to account for similar elementary cooperative behaviors (Braun et al, 2009), and to provide a general taxonomy of such behaviors (see the propositions along those lines by Jarrassé et al, 2012), possibly by developing a framework as complete as the one employing topological equivalence presented above. Thirdly there is a need to understand whether or not the synchronization between two persons possesses a special status among social coordinative behaviors.…”

Adaptive optimal control for coordination in physical human-robot interaction

“…Inspired by the insights from [17], we employ game theory to analyze human-robot interaction, and develop a specific framework which can be implemented in practical robot control. Besides this, we propose an adaptation law that automatically adjusts the role of the robot based on the measured interaction force, in order to achieve human-robot coordination.…”