Negotiation-based Human-Robot Collaboration via Augmented Reality

Background: 

There are a variety of robot platforms that have been developed for very different purposes. Some examples include: warehouse robots, indoor service robots, military robots, and rescue robots. Despite their capabilities of accomplishing complex tasks in the real world, these robots rarely collaborate with people. One of the main challenges in human-robot collaboration is the significant communication cost. More precisely, effective human-robot collaboration requires extensive communications on intentions in the form of planned future actions. Natural language is the most common communication channel in human community, but is less effective for human-robot interaction due to the limited bandwidth and ubiquitous ambiguity. Therefore, there is the need of creating novel technologies for efficient, accurate human-robot communication toward effective collaborations within human-robot teams. This research has the potential to significantly reduce the communication cost within human-robot teams, and is generally applicable to the above-mentioned robot application domains.

Technology Overview:

An augmented reality-driven, negotiation-based (ARN) framework for human-robot collaboration, where ARN supports planning-phase negotiations within human robot teams through a novel AR-based interface.

Advantages:

• In comparison to other channels for human-robot communication, our AR-based technology provides high bandwidth, low latency, and low ambiguity.
• This new technology is intuitive, and the training effort (to new human users) is minimum in comparison to traditional Human-Computer Interaction (HCI) technologies.