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Keisuke Nakamura

15 accepted papers

2023

GAN-Based Interactive Reinforcement Learning from Demonstration and Human Evaluative Feedback

ICRA 2023poster

Generative adversarial imitation learning (GAIL) — a general model-free imitation learning method, allows robots to directly learn policies from expert trajectories in large environments. However, GAIL shares the limitation of other imitation learning methods that they can seldom surpass the perform…

Cited by 10SourceScholar
2023

Sim-to-Real Policy and Reward Transfer with Adaptive Forward Dynamics Model

ICRA 2023poster

Deep reinforcement learning has shown promise in learning robust skills for robot control, but typically requires a large amount of samples to achieve good performance. Sim-to-real transfer learning has been developed to solve this problem, but the policy trained in simulation usually has unsatisfac…

Cited by 3SourceScholar
2022

Affective Behavior Learning for Social Robot Haru with Implicit Evaluative Feedback

IROS 2022poster

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…

Cited by 4SourceScholar
2022

Developing The Bottom-up Attentional System of A Social Robot

ICRA 2022poster

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…

Cited by 7SourceScholar
2021

Automating Behavior Selection for Affective Telepresence Robot

ICRA 2021poster

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…

Cited by 7SourceScholar
2021

Shaping Progressive Net of Reinforcement Learning for Policy Transfer with Human Evaluative Feedback

IROS 2021poster

Deep reinforcement learning has achieved significant success in many fields, but will confront sampling efficiency and safety problems when applying to robot control in the real world. Sim-to-real transfer learning was proposed to make use of samples in the simulation and overcome the gap between si…

Cited by 9SourceScholar
2020

A Holistic Approach in Designing Tabletop Robot’s Expressivity

ICRA 2020poster

Defining a robot's expressivity is a difficult task that requires thoughtful consideration of the potential of various robot modalities and a model of communication that humans understand. Humanoid and zoomorphic-designed robots can easily take cues from human and animals, respectively when designin…

Cited by 42SourceScholar
2016

Online simultaneous localization and mapping of multiple sound sources and asynchronous microphone arrays

IROS 2016poster

This paper presents an online method of simultaneous localization and mapping (SLAM) for estimating the positions of multiple moving sound sources and stationary robots and synchronizing microphone arrays attached to those robots. Since each robot with a microphone array can solely estimate the dire…

Cited by 18SourceScholar
2016

Robust sound source mapping using three-layered selective audio rays for mobile robots

IROS 2016poster

This paper investigates sound source mapping in a real environment using a mobile robot. Our approach is based on audio ray tracing which integrates occupancy grids and sound source localization using a laser range finder and a microphone array. Previous audio ray tracing approaches rely on all obse…

Cited by 11SourceScholar
2015

Interactive sound source localization using robot audition for tablet devices

IROS 2015poster

This paper investigates localization of sound sources in a real environment using a tablet device. For the localization, we use build-in sensors on a tablet device and additionally mount a cover with a microphone array. Because of the flat shape and limited sensor performance, the localization has m…

Cited by 5SourceScholar
2015

On-the-spot calibration of microphone array Transfer Functions for robot audition

ICRA 2015poster

This paper investigates the calibration of a microphone array based robot audition system, namely calibration of microphone array Transfer Functions (TFs). There are mainly two methods to obtain TFs: geometrical calculation and measurement. The geometrical calculation has difficulty in simulating ro…

Cited by 7SourceScholar
2015

Robot audition based Acoustic Event Identification using a Bayesian model considering spectral and temporal uncertainties

IROS 2015poster

To analyze auditory scenes of robots' surrounding environments, not only speeches but also non-speech sounds are important, which are spatially distributed and have different spectral and temporal characteristics. Thus, this paper investigates Acoustic Event Identification (AEI) which includes probl…

Cited by 9SourceScholar
2015

Temporal smearing compensation in reverberant environment for speech-based human-robot interaction

ICRA 2015poster

Speech-based human-robot interaction is often plagued with issues such as reverberation and changes in speaker position that impacts overall performance. In this paper, we show a method in compensating the joint effects of reverberation and the change in speaker position. The acoustic perturbation c…

Cited by 2SourceScholar
2015

Utilizing visual cues in robot audition for sound source discrimination in speech-based human-robot communication

IROS 2015poster

It is easy for human beings to discern whether an observed acoustic signal is a direct speech, reflected speech or noise through simple listening. Relying purely on acoustic cues is enough for human beings to discriminate between the different kinds of sound sources which is not straightforward for…

Cited by 6SourceScholar