21 citations · 61 across the 19 of their papers we have counts for
23 papers
Adaptive Question Generation for Ambiguous Robot Instructions Based on Information Gain and Human Cognitive Characteristics
Ryo Terashima, Yuga Yano, Hakaru Tamukoh
In this study, we propose an adaptive question generation mechanism that addresses uncertainty arising from ambiguous instructions. Natural-language instructions for service robots…
Real-Time Service Robot Replanning via Simple Button Interaction for Improved Task Success and User Experience
Ryo Terashima, Yuga Yano, Koshun Arimura +1
Service robots must respond to unexpected instructions in real-world environments. However, robots cannot detect all failures and exceptions during a task. To address these issues,…
Human-Centric Grasp State Assessment: Toward Transferring Subjective Evaluation to Robots
Ryohei Kobayashi, Kosei Isomoto, Yuga Yano +2
We propose a framework that transfers tacit human subjective criteria to robotic systems for the appropriate grasping of deformable objects. Achieving such behavior is challenging…
SaaF: Scene-Specific Ambiguity-Aware 3D Language Fields towards Interactive Real-World Object Retrieval
Yuga Yano, Daiju Kanaoka, Hakaru Tamukoh +1
We propose Scene-specific Ambiguity-aware 3D Language Fields (SaaF), a novel Gaussian Splatting-based 3D language field designed for interactive object retrieval in a given real-wo…
Hibikino-Musashi@Home 2025 Team Description Paper
Ryohei Kobayashi, Kosei Isomoto, Kosei Yamao +19
This paper provides an overview of the techniques employed by Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team developed a dat…
Techniques for Enhancing Memory Capacity of Reservoir Computing
Atsuki Yokota, Ichiro Kawashima, Yohei Saito +3
Reservoir Computing (RC) is a bio-inspired machine learning framework, and various models have been proposed. RC is a well-suited model for time series data processing, but there i…
Unified Understanding of Environment, Task, and Human for Human-Robot Interaction in Real-World Environments
Yuga Yano, Akinobu Mizutani, Yukiya Fukuda +3
To facilitate human--robot interaction (HRI) tasks in real-world scenarios, service robots must adapt to dynamic environments and understand the required tasks while effectively co…
Enhancing Neural Network Robustness Against Fault Injection Through Non-linear Weight Transformations
Ninnart Fuengfusin, Hakaru Tamukoh
Deploying deep neural networks (DNNs) in real-world environments poses challenges due to faults that can manifest in physical hardware from radiation, aging, and temperature fluctu…
Harden Deep Neural Networks Against Fault Injections Through Weight Scaling
Ninnart Fuengfusin, Hakaru Tamukoh
Deep neural networks (DNNs) have enabled smart applications on hardware devices. However, these hardware devices are vulnerable to unintended faults caused by aging, temperature va…
Hibikino-Musashi@Home 2024 Team Description Paper
Kosei Isomoto, Akinobu Mizutani, Fumiya Matsuzaki +25
This paper provides an overview of the techniques employed by Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team has developed a…
Haptic in-sensor computing device made of carbon nanotube-polydimethylsiloxane nanocomposites
Kouki Kimizuka, Saman Azhari, Shoshi Tokuno +5
The importance of haptic in-sensor computing devices has been increasing. In this study, we successfully fabricated a haptic sensor with a hierarchical structure via the sacrificia…
ManifoldNeRF: View-dependent Image Feature Supervision for Few-shot Neural Radiance Fields
Daiju Kanaoka, Motoharu Sonogashira, Hakaru Tamukoh +1
Novel view synthesis has recently made significant progress with the advent of Neural Radiance Fields (NeRF). DietNeRF is an extension of NeRF that aims to achieve this task from o…
Hibikino-Musashi@Home 2023 Team Description Paper
Tomoya Shiba, Akinobu Mizutani, Yuga Yano +25
This paper describes an overview of the techniques of Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team has developed a dataset…
Hibikino-Musashi@Home 2022 Team Description Paper
Tomoya Shiba, Tomohiro Ono, Shoshi Tokuno +27
Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in Japan in the Kitakyushu Science and Research Park. Since 2010, we have annually participated in the RoboC…
Hibikino-Musashi@Home 2018 Team Description Paper
Yutaro Ishida, Sansei Hori, Yuichiro Tanaka +14
Our team, Hibikino-Musashi@Home (the shortened name is HMA), was founded in 2010. It is based in the Kitakyushu Science and Research Park, Japan. We have participated in the RoboCu…
Hibikino-Musashi@Home 2019 Team Description Paper
Yuichiro Tanaka, Yutaro Ishida, Yushi Abe +12
Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in the Kitakyushu Science and Research Park, Japan. Since 2010, we have participated in the RoboCup@Home Jap…
Hibikino-Musashi@Home 2020 Team Description Paper
Tomohiro Ono, Yuichiro Tanaka, Yutaro Ishida +17
Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in Japan in the Kitakyushu Science and Research Park. Since 2010, we have annually participated in the RoboC…
An Efficient Hardware-Oriented Dropout Algorithm
Yoeng Jye Yeoh, Takashi Morie, Hakaru Tamukoh
This paper proposes a hardware-oriented dropout algorithm, which is efficient for field programmable gate array (FPGA) implementation. In deep neural networks (DNNs), overfitting o…
Network with Sub-Networks
Ninnart Fuengfusin, Hakaru Tamukoh
We introduce network with sub-networks, a neural network which its weight layers could be detached into sub-neural networks during inference. To develop weights and biases which co…
An Energy-efficient Time-domain Analog VLSI Neural Network Processor Based on a Pulse-width Modulation Approach
Masatoshi Yamaguchi, Goki Iwamoto, Hakaru Tamukoh +1
A time-domain analog-weighted-sum calculation model based on a pulse-width modulation (PWM) approach is proposed. The proposed calculation model can be applied to any types of netw…
A Time-domain Analog Weighted-sum Calculation Model for Extremely Low Power VLSI Implementation of Multi-layer Neural Networks
Quan Wang, Hakaru Tamukoh, Takashi Morie
A time-domain analog weighted-sum calculation model is proposed based on an integrate-and-fire-type spiking neuron model. The proposed calculation model is applied to multi-layer f…
Hibikino-Musashi@Home 2017 Team Description Paper
Sansei Hori, Yutaro Ishida, Yuta Kiyama +12
Our team Hibikino-Musashi@Home was founded in 2010. It is based in Kitakyushu Science and Research Park, Japan. Since 2010, we have participated in the RoboCup@Home Japan open comp…
Depth-Based Visual Servoing Using Low-Accurate Arm
Ludovic Hofer, Michio Tanaka, Hakaru Tamukoh +2
This paper proposes a visual-servoing method dedicated to grasping of daily-life objects. In order to obtain an affordable solution, we use a low-accurate robotic arm. Our method c…