13 accepted papers
We present the design, development, and evaluation of HREyes: biomimetic communication devices which use light to communicate information and, for the first time, gaze direction from AUVs to humans. First, we introduce two types of information displays using the HREye devices: active lucemes and ocu…
In this letter, we present SIREN: a novel audio-based communication system for underwater human-robot interaction. SIREN utilizes a surface transducer to produce sound by vibrating the frame of an underwater robot, essentially turning the robot's outer surface into the vibrating membrane of a speake
In this paper, we present a motion-based robotic communication framework that enables non-verbal communication among autonomous underwater vehicles (AUVs) and human divers. We design a gestural language for AUV-to-AUV communication which can be easily understood by divers observing the conversation…
Autonomous underwater vehicles (AUVs) have long lagged behind other types of robots in supporting natural communication modes for human-robot interaction. Due to the limitations of the environment, most AUVs use digital displays or topside human-in-the-loop communications as their primary or only co…
Direct communication between humans and autonomous underwater vehicles (AUVs) is a relatively under-explored area in human-robot interaction research, although many tasks (e.g., surveillance, inspection, and search-and-rescue) require close diver-robot collaboration. Suboptimal AUV positioning relat…
Autonomous Underwater Vehicles (AUVs) can be effective collaborators to human scuba divers in many applications, such as environmental surveying, mapping, or infrastructure repair. However, for these applications to be realized in the real world, it is essential that robots are able to both lead and…
Deep neural networks are the leading solution to the object detection problem. However, challenges arise when applying these networks to the kind of real-time, first-person video data that a robotic platform must process: specifically, detections may not be consistent from frame to frame, and object
Deep neural networks are the leading solution to the object detection problem. However, challenges arise when applying these networks to the kind of real-time, first-person video data that a robotic platform must process: specifically, detections may not be consistent from frame to frame, and object…
This paper presents an approach to address data scarcity problems in underwater image datasets for visual detection of marine debris. The proposed approach relies on a two-stage variational autoencoder (VAE) and a binary classifier to evaluate the generated imagery for quality and realism. From the…
In this paper we present the LoCO AUV, a Low-Cost, Open Autonomous Underwater Vehicle. LoCO is a general-purpose, single-person-deployable, vision-guided AUV, rated to a depth of 100 meters. We discuss the open and expandable design of this underwater robot, as well as the design of a simulator in G…
In this paper, we propose a novel method for underwater robot-to-human communication using the motion of the robot as “body language”. To evaluate this system, we develop simulated examples of the system's body language gestures, called kinemes, and compare them to a baseline system using flashing c…
Trash deposits in aquatic environments have a destructive effect on marine ecosystems and pose a long-term economic and environmental threat. Autonomous underwater vehicles (AUVs) could very well contribute to the solution of this problem by finding and eventually removing trash. This paper evaluate…
This letter explores the design and development of a class of robust diver detection algorithms for autonomous diver-following applications. By considering the operational challenges for underwater visual tracking in diverse real-world settings, we formulate a set of desired features of a generic di