Scalable target detection for large robot teams

Abstract

In this paper, we present an asynchronous display method, coined image queue, which allows operators to search through a large amount of data gathered by autonomous robot teams. We discuss and investigate the advantages of an asynchronous display for foraging tasks with emphasis on Urban Search and Rescue. The image queue approach mines video data to present the operator with a relevant and comprehensive view of the environment in order to identify targets of interest such as injured victims. It fills the gap for comprehensive and scalable displays to obtain a network-centric perspective for UGVs. We compared the image queue to a traditional synchronous display with live video feeds and found that the image queue reduces errors and operator's workload. Furthermore, it disentangles target detection from concurrent system operations and enables a call center approach to target detection. With such an approach we can scale up to very large multi-robot systems gathering huge amounts of data that is then distributed to multiple operators.

Human Swarm Interaction: An Experimental Study of Two Types of Interaction with Foraging Swarms

“…While it may seem obvious to have autonomous seeking of all detected information objects, it is worth noting that in most realistic applications humans operators are still responsible for determining whether a target of interest is present, especially when the sensor data is complex, e.g., video in a search & rescue mission (H. Wang et al, 2011).…”

“…In short, enabling human operators to control robot swarms with hundreds of robots, or more, is still an open problem. Currently, multi-robot approaches generally scale to at most ten's of robots per operator even when using state of the art mapping, path planning, target detection, and coordination algorithms to alleviate the load on the operator (H. Wang et al, 2011;J. Wang & Lewis, 2007).…”

A novel user-guided interface for robot search

“…There is a growing interest in human operator interfaces for robotic exploration and search in unknown areas [6], [9], [7]. Human operators play a key role in such missions, as the interpretation of camera images typically requires the visual perception skills of humans [9].…”

“…This has several advantages. First, it allows scaling up the number of robots with only a moderate increase to the operator's workload, since the operator no longer has to observe live video feeds from multiple robots [7]. It also overcomes communication constraints that often limit the ability to stream live video from the robots.…”

“…A leading approach automates this process, and automatically selects images for viewing, based on a utility value, which is computed by the image area that was not already seen [7]. Users can then view images according to that order, and navigate through images that were recorded near the selected image.…”