no code implementations • 20 Mar 2024 • Yusuke Mikami, Andrew Melnik, Jun Miura, Ville Hautamäki
We demonstrate experimental results with LLMs that address robotics task planning problems.
1 code implementation • 13 Jul 2023 • Oskar Natan, Jun Miura
To evaluate its performance, we conduct several tests by deploying the model to predict a set of driving records and perform real automated driving under three different conditions.
1 code implementation • 2 Mar 2023 • Shigemichi Matsuzaki, Hiroaki Masuzawa, Jun Miura
This paper describes a method of domain adaptive training for semantic segmentation using multiple source datasets that are not necessarily relevant to the target dataset.
no code implementations • 13 Aug 2022 • Shigemichi Matsuzaki, Hiroaki Masuzawa, Jun Miura
This paper describes a method of online refinement of a scene recognition model for robot navigation considering traversable plants, flexible plant parts which a robot can push aside while moving.
2 code implementations • 20 Jul 2022 • Oskar Natan, Jun Miura
In this work, we introduce DeepIPC, a novel end-to-end model tailored for autonomous driving, which seamlessly integrates perception and control tasks.
1 code implementation • 12 Apr 2022 • Oskar Natan, Jun Miura
Focusing on the task of point-to-point navigation for an autonomous driving vehicle, we propose a novel deep learning model trained with end-to-end and multi-task learning manners to perform both perception and control tasks simultaneously.
no code implementations • 21 Apr 2021 • Keishi Ishihara, Anssi Kanervisto, Jun Miura, Ville Hautamäki
This does not only improve the success rate of standard benchmarks, but also the ability to react to traffic lights, which we show with standard benchmarks.
no code implementations • 12 Feb 2021 • Shigemichi Matsuzaki, Jun Miura, Hiroaki Masuzawa
The core of our idea is to use multiple rich image datasets of different environments with segmentation labels to generate pseudo-labels for the target images to effectively transfer the knowledge from multiple sources and realize a precise training of semantic segmentation.
no code implementations • 5 Oct 2019 • Motoki Kojima, Jun Miura
This paper describes a method of estimating the intention of a user's motion in a robot tele-operation scenario.