ACTICIPATE · Action understanding in human and robot dyadic interaction
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2017-06-01 → 2018-08-31
- EU contribution
- €100,397
- Participants
- 1
- Scheme
- MSCA-IF-EF-ST
Lines connect the coordinator with its partners.
Results in brief
Action understanding in human and robot dyadic interaction
ACTICIPATE addressed the design of the robot’s behaviour that will share workspaces and co-work with humans in the future. The behaviour modelling relied on human experiments to learn the important cues in dyadic human-human interaction. It allowed us to develop a behaviour model that controls humanoid robot upper body motion in dynamic environments, during reaching and manipulation tasks, and at the same time to understand, predict and anticipate the actions of a human co-worker, as needed in manufacturing, assistive and service robotics, and domestic applications. The dyadic interaction scenarios call for the following capabilities that are tackled in ACTICIPATE: (i) a motion generation mechanism to allow the robot to perform legible movements easily understandable to human (ii) a framework to coordinate movements of head, eyes and arm in a way similar to human movements, and model the action/movement coupling between co-workers in dyadic interaction tasks. (iii) the ability to understand and anticipate human actions, based on a common motor system/model. There are numerous reasons for the development of such robots, and equally numerous capabilities that future robots yet need to acquire before cohabitation with humans becomes a reality. Among many, human-like nonverbal interpersonal interaction model holds the great potential to pave the way to successful utilization of the robot co-workers in a dynamic manufacturing environment. Interaction model has two-fold utilization. It is used to decode the observed motions of the others and at the same time to plan the robot’s actions and coordinate the motion execution of eyes, head and arms.
Data: CORDIS, © European Union
Project objective
Humans have fascinating skills for grasping and manipulation of objects, even in complex, dynamic environments, and execute coordinated movements of the head, eyes, arms, and hands, in order to accomplish everyday tasks. When working on a shared space, during dyadic interaction tasks, humans engage in non-verbal communication, by understanding and anticipating the actions of working partners, and coupling their actions in a meaningful way. The key to this mind-boggling performance is two-fold: (i) a capacity to adapt and plan the motion according to unexpected events in the environment, (ii) and the use of a common motor repertoire and action model, to understand and anticipate the actions and intentions of others as if they were our own. Despite decades of progress, robots are still far from the level of performance that would enable them to work with humans in routine activities.ACTICIPATE addresses the challenge of designing robots that can share workspaces and co-work with humans. We rely on human experiments to learn a model/controller that allows a humanoid to generate and adapt its upper body motion, in dynamic environments, during reaching and manipulation tasks, and to understand, predict and anticipate the actions of a human co-worker, as needed in manufacturing, assistive and service robotics, and domestic applications.These application scenarios call for three main capabilities that will be tackled in ACTICIPATE: a motion generation mechanism (primitives), with a built-in capacity for instant reaction to changes in dynamic environments; a framework to combine primitives and execute coordinated movements of head, eyes, arm and hand, in a way similar (thus predictable) to human movements, and model the action/movement coupling between co-workers in dyadic interaction tasks; and the ability to understand and anticipate human actions, based on a common motor system/model that is also used to synthesize the robot’s goal-directed actions in a natural way.
Original text from CORDIS.
Participants
- INSTITUTO SUPERIOR TECNICO · LisboaCoordinatorPortugal
Links
Data: CORDIS, © European Union