10 accepted papers
The effective deployment of robots in risky and crowded environments (RCE) requires the specification of robot plans that are consistent with humans' behaviors. As is well known, humans perceive uncertainty and risk in a biased way, which can lead to a diversity of actions and expectations when inte
The emergency department (ED) is a safety-critical environment in which healthcare workers (HCWs) are overburdened, overworked, and have limited resources, especially during the COVID-19 pandemic. One way to address this problem is to explore the use of robots that can support clinical teams, e.g.,…
As robots work with human teams, they will be expected to fluently coordinate with them. While people are adept at coordination and real-time adaptation, robots still lack this skill. In this paper, we introduce TANDEM: Temporal Anticipation and Adaptation for Machines, a series of neurobiologically…
A key challenge in robotics is the capability to perceive unseen objects, which can improve a robot's ability to learn from and adapt to its surroundings. One approach is to employ unsupervised, salient object discovery methods, which has shown promise in the computer vision literature. However, mos
In safety-critical environments, robots need to reliably recognize human activity to be effective and trust-worthy partners. Since most human activity recognition (HAR) approaches rely on unimodal sensor data (e.g. motion capture or wearable sensors), it is unclear how the relationship between the s…
The recent emergence of object proposal algorithms in the computer vision community shows great promise to addressing difficult problems in robotic such as object discovery and salient object detection. However, it is difficult to determine how these algorithms actually perform for real-world robot…
In this work, we present a novel non-visual HAR system that achieves state-of-the-art performance on realistic SCE tasks via a single wearable sensor. We leverage surface electromyography and inertial data from a low-profile wearable sensor to attain performant robot perception while remaining unobt…
As robots enter human environments, they will be expected to collaborate and coordinate their actions with people. In order for robots to become more fluent at this, particularly in groups, robots must be able to recognize, understand, and anticipate coordinated human activities. However, how robots
This paper introduces Salient Depth Partitioning (SDP), a depth-based region cropping algorithm devised to be easily adapted to existing detection algorithms. SDP is designed to give robots a better sense of visual attention, and to reduce the processing time of pedestrian detectors. In contrast to…
As robots enter human spaces, unique perception challenges are emerging. Sensing human activity, adapting to highly dynamic environments, and acting coherently and contingently is challenging when robots transition from structured environments to human-centric ones. We approach this problem by emplo…