32 accepted papers
Robots are becoming essential in human environments, requiring them to behave in a socially compliant manner. Although previous learning-based methods have shown potential in social navigation, most have treated pedestrians as individuals, failing to account for group level interactions. Additionall
Navigating unknown three-dimensional (3D) rugged environments is challenging for multi-robot systems. Traditional discrete systems struggle with rough terrain due to limited individual mobility, while modular systems—where rigid, controllable constraints link robot units—improve traversal but suffer
2D forward looking sonar (FLS) has gained widespread application in underwater robotics research, primarily due to its capacity to produce high-resolution images in diverse aquatic environments. This study deals with pose estimation with given 3D positions and corresponding 2D pixels, which is a fun
A system is expected to facilitate coordination among multiple construction machines or robots, enabling them to adaptively perform various tasks in disaster sites and unknown environments. Prior research has generally adopted a model-based approach to designing cooperative behavior. However, it is…
We approach designing a state-space model for deep learning applications through its dual representation, the *transfer function*, and uncover a highly efficient sequence parallel inference algorithm that is *state-free*: unlike other proposed algorithms, state-free inference does not incur any sign…
This letter presents Switch-SLAM, switching-based LiDAR-inertial-visual SLAM for degenerate environments, designed to tackle the challenges in degenerate environments for LiDAR and visual SLAM. Switch-SLAM achieves high robustness and accuracy by utilizing a switching structure that transitions from
Mobile robots functioning in human environments should behave with a secure and socially-compliant manner. Although many studies have revealed the effectiveness of Deep Reinforcement Learning (DRL) in robot navigation, most of them can only handle the presence of human as independent individuals. Fa…
2D forward-looking sonar is a crucial sensor for underwater robotic perception. A well-known problem in this field is estimating missing information in the elevation direction during sonar imaging. There are demands to estimate 3D information per image for 3D mapping and robot navigation during fly-…
Mobile robot navigation in a human-populated environment has been of great interest to the research community in recent years, referred to as crowd navigation. Currently, offline reinforcement learning (RL)-based method has been introduced to this domain, for its ability to alleviate the sim2real ga…
Retrieving the missing dimension information in acoustic images from 2D forward-looking sonar is a well-known problem in the field of underwater robotics. There are works attempting to retrieve 3D information from a single image which allows the robot to generate 3D maps with fly-through motion. How…
We detail a novel class of implicit neural models. Leveraging time-parallel methods for differential equations, Multiple Shooting Layers (MSLs) seek solutions of initial value problems via parallelizable root-finding algorithms. MSLs broadly serve as drop-in replacements for neural ordinary differe…
A novel method to estimate the missing dimension in 2D acoustic images for 3D reconstruction is proposed in this paper. Acoustic cameras can acquire high resolution 2D images in underwater environment insusceptible to water turbidity and light condition. However, the formulation of acoustic images l
Effective control and prediction of dynamical systems require appropriate handling of continuous-time and discrete, event-triggered processes. Stochastic hybrid systems (SHSs), common across engineering domains, provide a formalism for dynamical systems subject to discrete, possibly stochastic, stat…
In this study, we present a method for all-around depth estimation from multiple omnidirectional images for indoor environments. In particular, we focus on plane-sweeping stereo as the method for depth estimation from the images. We propose a new icosahedron-based representation and ConvNets for omn…
ACMarker is an acoustic camera-based fiducial marker system designed for underwater environments. Optical camera-based fiducial marker systems have been widely used in computer vision and robotics applications such as augmented reality (AR), camera calibration, and robot navigation. However, in unde
Continuous deep learning architectures have recently re-emerged as Neural Ordinary Differential Equations (Neural ODEs). This infinite-depth approach theoretically bridges the gap between deep learning and dynamical systems, offering a novel perspective. However, deciphering the inner working of the…
The infinite-depth paradigm pioneered by Neural ODEs has launched a renaissance in the search for novel dynamical system-inspired deep learning primitives; however, their utilization in problems of non-trivial size has often proved impossible due to poor computational scalability. This work paves th…
Awareness of surrounding and prediction of dangerous situations is essential for autonomous mobile robots, especially during navigation in a human-populated environment. To cope with safety issues, state-of-the-art works have focused on pedestrian detection, tracking, and trajectory prediction. Howe
Sit-to-stand (STS) motion is an important daily activity and many post-stroke patients have difficulty in performing the STS motion. Post-stroke patients who can perform STS independently, still utilize four muscle synergies (synchronized muscle activation) as seen in healthy people. In addition, te
In this letter, we propose a novel approach for fusing information from multiple access points in order to enhance WiFi-based self-localization. A common approach for designing WiFi-based localization systems is to learn location-to-signal strength mappings for each access point in an environment. E
Spherical cameras, which can acquire all-round information, are effective to estimate rotation for robotic applications. Recently, Convolutional Neural Networks have shown great robustness in solving such regression problems. However they are designed for planar images and cannot deal with the non-u…
Stroke patients suffer from declined physical ability, and it is important to analyze rehabilitation intervention and clarify its effect on the motion of patients. In this study, the effect of intervention on the standing-up motion of stroke patients is investigated. First, the intervention timing o
Efficient diagnosis of concrete structures is a growing issue in modern societies where concrete is an omnipresent material. The hammering test is a traditional nondestructive testing method that has been employed in the field for a long time and for which automation is highly desirable. The problem
Localization is an important task for mobile service robots in indoor spaces. In this research, we propose a novel technique for indoor localization using a spherical camera. Spherical cameras can obtain a complete view of the surroundings allowing the use of global environmental information. We tak…
We propose a new detection method to predict a vehicle's trajectory and use it for detecting lane changes of surrounding vehicles. According to the previous research, more than 90% of the car crashes are caused by human errors, and lane changes are the main factor. Therefore, if a lane change can be
Spherical cameras are widely used due to their full 360$^\circ$ fields of view. However, a common but severe problem is that anything carrying the camera is always included in the view, occluding visual information. In this letter, we propose a novel method to remove such occlusions in videos taken
This paper introduces a new methodology of robotic hammering inspection for the maintenance of social infrastructures. In particular, the estimation of material defect conditions, such as delamination depth of concrete, is focused upon. Development of an automated diagnosis methodology is necessary
Indoor robot localization systems using wireless signal measurements have gained popularity in recent years, as wireless Local Area Networks can be found practically everywhere. In this field, a popular approach is the use of fingerprinting techniques, such as Gaussian Processes. In our approach, we…
It is important to understand the mechanism of human standing-up motion to improve the declined physical ability of the elderly people. This study employs the concept of muscle synergies (modular structure of coordinative muscle activation) to understand how humans coordinate their muscles to achiev…
We present a novel rough terrain traversability analysis method for mobile robot navigation. We focused on the scenario of mobile robot operation in a disaster environment with limited sensor data. The robot builds a map in real time and analyzes the terrain traversability of its surrounding environ…
An automated diagnosis methodology is necessary for the maintenance of superannuated social infrastructures. In this context, the hammering test is an efficient inspection method, and it has been widely used because of the resulting accuracy and efficiency of operation. While robotic automation of t…
Three-dimensional (3D) measurement is an important means for robots to acquire information about their environment. Structure from Motion is one of these 3D measurement methods. The 3D reconstruction of objects in the environment can be obtained from pictures captured with single camera in Structure…