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Issue 4 • April-2025
Showing 1-25 of 116
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A Portable Autonomous Underwater Vehicle With Multi-Thruster Propulsion: Design, Development, and Vision-Based Tracking Control
Publication Year: 2025,Page(s):3046 - 3053
Autonomous underwater vehicles (AUVs) play a pivotal role in the exploration of marine resources. With the increasing complexity of underwater tasks, conventional torpedo-shaped AUVs exhibit significant limitations, particularly in complex and dynamic environments, due to restricted lateral translation and in-place rotation capabilities. To address these challenges, this letter introduces OpenAUV,...Show More
H-PCC: Point Cloud Compression With Hybrid Mode Selection and Content Adaptive Down-Sampling
Publication Year: 2025,Page(s):3054 - 3061
LiDAR sensors are integral to autonomous driving and augmented reality applications, providing essential depth information. However, managing the substantial volume of LiDAR point cloud data is crucial for practical application, necessitating efficient compression algorithms. Similar to other data compression domains, point cloud compression aims to spatially and temporally decorrelate information...Show More
Human-in-the-Loop Optimization for Knee Exoskeleton Flexion Assistance
Zhipeng Wang;Baichun Wei;Zhen Ding;Jianfei Zhu;Lianpeng Zhang;Xiangduan Zeng;Chunzhi Yi
Publication Year: 2025,Page(s):3062 - 3069
Human-in-the-loop optimization (HILO) has been used to identify subject-specific assistive strategies and improve the performance of wearable exoskeletons. However, there is still a gap in research on HILO regarding knee exoskeleton flexion assistance. We present a HILO methodology that optimizes the flexion torque delivered by the knee exoskeleton. The cooperation mechanism of flexor and antagoni...Show More
Hybrid Iterative Linear Quadratic Estimation: Optimal Estimation for Hybrid Systems
Publication Year: 2025,Page(s):3070 - 3077
In this letter we present Hybrid iterative Linear Quadratic Estimation (HiLQE), an optimization based offline state estimation algorithm for hybrid dynamical systems. We utilize the saltation matrix, a first order approximation of the variational update through an event driven hybrid transition, to calculate gradient information through hybrid events in the backward pass of an iterative linear qua...Show More
Gaze-Guided Robotic Vascular Ultrasound Leveraging Human Intention Estimation
Publication Year: 2025,Page(s):3078 - 3085
Medical ultrasound has been widely used to examine vascular structure in modern clinical practice. However, traditional ultrasound examination often faces challenges related to inter- and intra-operator variation. The robotic ultrasound system (RUSS) appears as a potential solution for such challenges because of its superiority in stability and reproducibility. Given the complex anatomy of human v...Show More
SDPENet: A Lightweight Spacecraft Pose Estimation Network With Discrete Euler Angle Probability Distribution
Publication Year: 2025,Page(s):3086 - 3093
Utilizing deep learning techniques for spacecraft pose estimation enables using low-cost sensors like monocular cameras. However, the existing methods have drawbacks, such as complex models or low estimation accuracy. Therefore, this letter proposes the Spacecraft Discrete Pose Estimation Network (SDPENet). Firstly, we design a feature fusion network and a pose estimation head applicable to the sp...Show More
Real-Time Excavation Trajectory Modulation for Slip and Rollover Prevention
ChangU Kim;Bukun Son;Minhyeong Lee;Hyelim Choi;Seokhyun Hong;Minsung Kang;Jihyun Moon;Dongmok Kim;Dongjun Lee
Publication Year: 2025,Page(s):3094 - 3101
We propose a novel real-time excavation trajectory modulation framework on a slope for an autonomous excavator with a low-level digital kinematic control as common for hydraulic industrial excavators. Excavation on a slope is challenging because of a higher risk of slips and rollovers. To deal with this, we propose a real-time excavation trajectory modulation framework based on slope tangential/no...Show More
LatentBKI: Open-Dictionary Continuous Mapping in Visual-Language Latent Spaces With Quantifiable Uncertainty
Joey Wilson;Ruihan Xu;Yile Sun;Parker Ewen;Minghan Zhu;Kira Barton;Maani Ghaffari
Publication Year: 2025,Page(s):3102 - 3109
This letter introduces a novel probabilistic mapping algorithm, LatentBKI, which enables open-vocabulary mapping with quantifiable uncertainty. Traditionally, semantic mapping algorithms focus on a fixed set of semantic categories which limits their applicability for complex robotic tasks. Vision-Language (VL) models have recently emerged as a technique to jointly model language and visual feature...Show More
Developing a Vision and Contact Sensor-Based Android-to-Human Touch System That Enables Face and Arm Touch
Aidan E. Fox-Tierney;Kurima Sakai;Masahiro Shiomi;Takashi Minato;Hiroshi Ishiguro
Publication Year: 2025,Page(s):3110 - 3117
Mainstream use of AI has enabled human-like conversations with machines. Despite the perceived naturalness of these interactions, they are limited to 2D screens. Androids offer us an opportunity to explore the third dimension, touch, with a human-centered approach. In this work we developed and evaluated a system that lays some of the groundwork for future dialogues with these androids. While ther...Show More
Boost Query-Centric Network Efficiency for Multi-Agent Motion Forecasting
Publication Year: 2025,Page(s):3118 - 3125
Real-time multi-agent motion forecasting is essential for autonomous vehicles to safely navigate on urban roads. Recent advancements in this field exhibit the superior performance of Query-Centric Networks for large-scale data and long-term prediction. However, these methods often suffer from high space and time complexity, which limits their practicality and impedes further research. E.g., traini...Show More
Boost Query-Centric Network Efficiency for Multi-Agent Motion Forecasting
Year: 2025 | Volume: 10 | Issue: 4
PRISM-TopoMap: Online Topological Mapping With Place Recognition and Scan Matching
Kirill Muravyev;Alexander Melekhin;Dmitry Yudin;Konstantin Yakovlev
Publication Year: 2025,Page(s):3126 - 3133
Mapping is one of the crucial tasks enabling autonomous navigation of a mobile robot. Conventional mapping methods output a dense geometric map representation, e.g. an occupancy grid, which is not trivial to keep consistent for prolonged runs covering large environments. Meanwhile, capturing the topological structure of the workspace enables fast path planning, is typically less prone to odometry ...Show More
CAFuser: Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes
Publication Year: 2025,Page(s):3134 - 3141
Leveraging multiple sensors is crucial for robust semantic perception in autonomous driving, as each sensor type has complementary strengths and weaknesses. However, existing sensor fusion methods often treat sensors uniformly across all conditions, leading to suboptimal performance. By contrast, we propose a novel, condition-aware multimodal fusion approach for robust semantic perception of drivi...Show More
Wavelet Movement Primitives: A Unified Framework for Learning Discrete and Rhythmic Movements
Publication Year: 2025,Page(s):3142 - 3149
Real-world tasks often require combinations of both discrete and rhythmic movements. However, most of current methods can only address one of them. This letter proposes a unified framework, Wavelet Movement Primitives (WMPs), which are built on Probabilistic Movement Primitives (ProMPs) integrated with Discrete Wavelet Transform (DWT), to model and learn both discrete and rhythmic trajectories fro...Show More
Online Friction Coefficient Identification for Legged Robots on Slippery Terrain Using Smoothed Contact Gradients
Publication Year: 2025,Page(s):3150 - 3157
This letter proposes an online friction coefficient identification framework for legged robots on slippery terrain. The approach formulates the optimization problem to minimize the sum of residuals between actual and predicted states parameterized by the friction coefficient in rigid body contact dynamics. Notably, the proposed framework leverages the analytic smoothed gradient of contact impulses...Show More
BEVCon: Advancing Bird's Eye View Perception With Contrastive Learning
Publication Year: 2025,Page(s):3158 - 3165
We present BEVCon, a simple yet effective contrastive learning framework designed to improve Bird's Eye View (BEV) perception in autonomous driving. BEV perception offers a top-down-view representation of the surrounding environment, making it crucial for 3D object detection, segmentation, and trajectory prediction tasks. While prior work has primarily focused on enhancing BEV encoders and task-sp...Show More
DeRi-IGP: Learning to Manipulate Rigid Objects Using Deformable Linear Objects via Iterative Grasp-Pull
Publication Year: 2025,Page(s):3166 - 3173
Robotic manipulation of rigid objects via deformable linear objects (DLO) such as ropes is an emerging field of research with applications in various rigid object transportation tasks. A few methods that exist in this field suffer from limited robot action and operational space, poor generalization ability, and expensive model-based development. To address these challenges, we propose a universall...Show More
Robotic Arm Platform for Multi-View Image Acquisition and 3D Reconstruction in Minimally Invasive Surgery
Alexander Saikia;Chiara Di Vece;Sierra Bonilla;Chloe He;Morenike Magbagbeola;Laurent Mennillo;Tobias Czempiel;Sophia Bano;Danail Stoyanov
Publication Year: 2025,Page(s):3174 - 3181
Minimally invasive surgery (MIS) offers significant benefits, such as reduced recovery time and minimised patient trauma, but poses challenges in visibility and access, making accurate 3D reconstruction a significant tool in surgical planning and navigation. This work introduces a robotic arm platform for efficient multi-view image acquisition and precise 3D reconstruction in MIS settings. We adap...Show More
Fast Shortest Path Polyline Smoothing With $G^{1}$ Continuity and Bounded Curvature
Patrick Pastorelli;Simone Dagnino;Enrico Saccon;Marco Frego;Luigi Palopoli
Publication Year: 2025,Page(s):3182 - 3189
In this work, we propose the Dubins Path Smoothing (DPS) algorithm, a novel and efficient method for smoothing polylines in motion planning tasks. DPS applies to motion planning of vehicles with bounded curvature. In the letter, we show that the generated path: 1) has minimal length, 2) is $G^{1}$ continuous, and 3) is collision-free by construction, under mild hypotheses. We compare our solution ...Show More
Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications
Xilun Zhang;Shiqi Liu;Peide Huang;William Jongwon Han;Yiqi Lyu;Mengdi Xu;Ding Zhao
Publication Year: 2025,Page(s):3190 - 3197
Sim-to-real transfer remains a significant challenge in robotics due to the discrepancies between simulated and real-world dynamics. Traditional methods like Domain Randomization often fail to capture fine-grained dynamics, limiting their effectiveness for precise control tasks. In this work, we propose a novel approach that dynamically adjusts simulation environment parameters online using in-con...Show More
Whole-Body Teleoperation for Mobile Manipulation at Zero Added Cost
Daniel Honerkamp;Harsh Mahesheka;Jan Ole von Hartz;Tim Welschehold;Abhinav Valada
Publication Year: 2025,Page(s):3198 - 3205
Demonstration data plays a key role in learning complex behaviors and training robotic foundation models. While effective control interfaces exist for static manipulators, data collection remains cumbersome and time intensive for mobile manipulators due to their large number of degrees of freedom. While specialized hardware, avatars, or motion tracking can enable whole-body control, these approach...Show More
Mode-Unified Intent Estimation of a Robotic Prosthesis Using Deep-Learning
Hanjun Kim;Dawit Lee;Jairo Y. Maldonado-Contreras;Sixu Zhou;Kinsey R. Herrin;Aaron J. Young
Publication Year: 2025,Page(s):3206 - 3213
Traditional robotic knee-ankle prostheses categorize ambulation modes such as level walking, ramps, and stairs. However, human movement scales continuously across various states rather than discretely, making traditional mode classifiers inadequate for accurate intent recognition. This letter proposes a mode-unified intent recognition strategy that continuously estimates terrain slopes across five...Show More
Asymptotically Optimal Path Planning With an Approximation of the Omniscient Set
Publication Year: 2025,Page(s):3214 - 3221
The asymptotically optimal version of Rapidly-exploring Random Tree (RRT*) is often used to find optimal paths in a high-dimensional configuration space. The well-known issue of RRT* is its slow convergence towards the optimal solution. A possible solution is to draw random samples only from a subset of the configuration space that is known to contain configurations that can improve the cost of th...Show More
‘What Did the Robot Do in My Absence?’ Video Foundation Models to Enhance Intermittent Supervision
Publication Year: 2025,Page(s):3222 - 3229
This paper investigates the use of Video Foundation Models (ViFMs) for generating robot data summaries to enhance intermittent human supervision of robot teams. We propose a novel framework that produces both generic and query-driven summaries of long-duration robot vision data in three modalities: storyboards, short videos, and text. Through a user study involving 30 participants, we evaluate the...Show More
Heuristic Search for Path Finding With Refuelling
Shizhe Zhao;Anushtup Nandy;Howie Choset;Sivakumar Rathinam;Zhongqiang Ren
Publication Year: 2025,Page(s):3230 - 3237
This letter considers a generalization of the Path Finding (PF) problem with refuelling constraints referred to as the Gas Station Problem (GSP). Similar to PF, given a graph where vertices are gas stations with known fuel prices, and edge costs are the gas consumption between the two vertices, GSPseeks a minimum-cost path from the start to the goal vertex for a robot with a limited gas tank and a...Show More
A Hybrid Variable-Stiffness Soft Back Support Device
Rohan Khatavkar;The Bach Nguyen;Yuanhao Chen;Hyunglae Lee;Jiefeng Sun
Publication Year: 2025,Page(s):3238 - 3245
Back support devices(BSDs) have the potential to mitigate overexertion in industrial tasks and also to provide assistance to people with weak back muscle strength in daily activity. While state-of-the-art active BSDs can offer a high assistive force, they are bulky and heavy, making them uncomfortable for daily use. On the contrary, passive BSDs are compact but need manual adjustment to be versati...Show More
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