8 accepted papers
Retrieving CAD models for real-world object scans enhances object-level mapping, providing a nuanced spatial understanding crucial for precise interactions in robotics or mixed reality. Commonly, CAD model retrieval is performed by matching features learned in Euclidean space. However, learning disc…
Given its wide application in robotics, point cloud registration is a widely researched topic. Conventional methods aim to find a rotation and translation that align two point clouds in 6 degrees of freedom (DoF). However, certain tasks in robotics, such as category-level pose estimation, involve no…
We propose a human-in-the-loop reinforcement learning mechanism to help robots learn emotional behavior. Unlike the previous methods of providing explicit feedback via pressing keyboard buttons or mouse clicks, we provide a more natural way for ordinary people to train social robots how to perform s…
This paper describes the development of a 3- stage signalling framework to trigger a social robot's bottom- up reactive behavior inspired by a biological model. In the first stage, low-level firing of stimuli due to external sources is constructed through perception grounding. This is followed by a…
We introduce a novel stacked ensemble classifier for the unconstrained recognition of known and unknown gestural input data in nonverbal communication with a social robot. The architecture utilizes three separate CNNs of different expected data input size and combines their output predictions to a u…
The tabletop robot Haru, used for affective telepresence research, enables a teleoperator to communicate affects from a distance. The robot’s expressiveness offers myriad ways of communicating affects through the execution of emotive routines. The teleoperator reacts to input modalities such as the…
In this paper we develop a gestural communication perception system for a social robot companion that is able to autonomously learn novel gestures on-the-fly. The system constantly tracks human gestural activities with a camera and evaluates the performed gestures under an open-set assumption. This…
We introduce a novel technique for the automatic detection of word boundaries within continuous sentence expressions in Japanese Sign Language from three-dimensional body joint positions. First, the flow of signed sentence data within a temporal neighborhood is determined utilizing the spatial corre…