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Issue 99
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Intent Prediction-Driven Model Predictive Control for UAV Planning and Navigation in Dynamic Environments
Publication Year: 2025,Page(s):1 - 8
Aerial robots can enhance construction site productivity by autonomously handling inspection and mapping tasks. However, ensuring safe navigation near human workers remains challenging. While navigation in static environments has been well studied, navigating dynamic environments remains open due to challenges in perception and planning. Payload limitations restrict the robots to using cameras wit...Show More
CPG-Based Manipulation With Multi-Module Origami Robot Surface
Yuhao Jiang;Serge El Asmar;Ziqiao Wang;Serhat Demirtas;Jamie Paik
Publication Year: 2025,Page(s):1 - 8
Robotic manipulators often face challenges in handling objects of different sizes and materials, limiting their effectiveness in practical applications. This issue is particularly pronounced when manipulating meter-scale objects or those with varying stiffness, as traditional gripping techniques and strategies frequently prove inadequate. In this letter, we introduce a novel surface-based multi-mo...Show More
Object navigation tasks require agents to locate target objects within unfamiliar indoor environments. However, the first-person perspective inherently imposes limited visibility, complicating global planning. Hence, it becomes imperative for the agent to cultivate an efficient visual representation from this restricted viewpoint. To address this, we introduce a temporal scene-object graph (TSOG) ...Show More
Fixed-time Sliding Mode-based Adaptive Path Tracking Control of Maize Plant Protection Robot via Extreme Learning Machine
Publication Year: 2023,Page(s):1 - 8
Cited by: Papers (4)
During the maize middle and late periods, the soil between rows is soft and also involved with weeds and straw. When the plant protection robot (PPR) moves on the soil, there exists uncertain shear perturbation because of the shear action and pressure subsidence, leading to the difficulty of the controller design. In this work, we propose an adaptive path tracking control (PTC) considering disturb...Show More
Bi-phase Episodic Memory-Guided Deep Reinforcement Learning for Robot Skills
Publication Year: 2024,Page(s):1 - 8
Deep reinforcement learning has significant advantages in the field of robot skill learning, however it usually cannot make good use of experience. In this paper, a Bi-phase Episodic Memory Guided (BEMG) method for speeding up the learning process of DRL and solving the problem of sparse reward is proposed, which brings a large learning speed increasing of robotic operation skills acquisition thro...Show More
RID-Net: A Hybrid MLP-Transformer network for Robust Point Cloud Registration
Panfei Cheng;Hongshan Yu;Changxiang Liu;Kan Luo;Naveed Akhtar;Xieyuanli Chen
Publication Year: 2025,Page(s):1 - 8
The robustness of correspondence-based point cloud registration relies on transformation invariance and intrinsic distinctiveness of the descriptors computed for registration. However, for challenging scenarios with different objects having similar local geometry and low point cloud overlap, existing descriptors struggle to retain these properties. This inevitably leads to a considerable loss in m...Show More
Co-Fix3D: Enhancing 3D Object Detection with Collaborative Refinement
Wenxuan Li;Qin Zou;Chi Chen;Bo Du;Long Chen;Jian Zhou;Hongkai Yu
Publication Year: 2025,Page(s):1 - 8
3D object detection in driving scenarios is particularly challenging due to factors such as sensor noise, occlusions, and the inherent sparsity of LiDAR point clouds, which can lead to the loss or incompleteness of key features, in turn affecting perception performance. To address these challenges, we propose Co-Fix3D, an advanced detection framework that integrates Local and Global Enhancement (L...Show More
CSDO: Enhancing Efficiency and Success in Large-Scale Multi-Vehicle Trajectory Planning
Yibin Yang;Shaobing Xu;Xintao Yan;Junkai Jiang;Jianqiang Wang;Heye Huang
Publication Year: 2024,Page(s):1 - 8
This paper presents an efficient algorithm, naming Centralized Searching and Decentralized Optimization (CSDO), to find feasible solution for large-scale Multi-Vehicle Trajectory Planning (MVTP) problem. Due to the intractable growth of non-convex constraints with the number of agents, exploring various homotopy classes that imply different convex domains, is crucial for finding a feasible solutio...Show More
H-MaP: An Iterative and Hybrid Sequential Manipulation Planner
Berk Cicek;Arda Sarp Yenicesu;Cankut Bora Tuncer;Kutay Demiray;Ozgur S. Oguz
Publication Year: 2025,Page(s):1 - 8
This paper introduces H-MaP, a hybrid sequential manipulation planner that addresses complex tasks requiring both sequential actions and dynamic contact mode switches. Our approach reduces configuration space dimensionality by decoupling object trajectory planning from manipulation planning through object-based waypoint generation, informed contact sampling, and optimization-based motion planning....Show More
CSCPR: Cross-Source-Context Indoor RGB-D Place Recognition
Jing Liang;Zhuo Deng;Zheming Zhou;Min Sun;Omid Ghasemalizadeh;Cheng-Hao Kuo;Arnie Sen;Dinesh Manocha
Publication Year: 2025,Page(s):1 - 8
We extend our previous work, PoCo [1], and present a new algorithm, Cross-Source-Context Place Recognition (CSCPR), for RGB-D indoor place recognition that integrates global retrieval and reranking into an end-to-end model and keeps the consistency of using Context-of-Clusters (CoCs) [2] for feature processing. Unlike prior approaches that primarily focus on the RGB domain for place recognition re...Show More
ActiveGS: Active Scene Reconstruction Using Gaussian Splatting
Liren Jin;Xingguang Zhong;Yue Pan;Jens Behley;Cyrill Stachniss;Marija Popović
Publication Year: 2025,Page(s):1 - 8
Robotics applications often rely on scene reconstructions to enable downstream tasks. In this work, we tackle the challenge of actively building an accurate map of an unknown scene using an RGB-D camera on a mobile platform. We propose a hybrid map representation that combines a Gaussian splatting map with a coarse voxel map, leveraging the strengths of both representations: the high-fidelity scen...Show More
Spatiotemporal Multi-Camera Calibration using Freely Moving People
Publication Year: 2025,Page(s):1 - 8
We propose a novel method for spatiotemporal multi-camera calibration using freely moving people in multi-view videos. Since calibrating multiple cameras and finding matches across their views are inherently interdependent, performing both in a unified framework poses a significant challenge. We address these issues as a single registration problem of matching two sets of 3D points, leveraging hum...Show More
Reconfigurable Soft Pneumatic Actuators Using Multi-Material Self-Healing Polymers
Shota Kosaka;Kentaro Kimura;Seiichi Yamamoto;Hiroki Ishizuka;Yoichi Masuda;Parinya Punpongsanon;Sei Ikeda;Osamu Oshiro
Publication Year: 2025,Page(s):1 - 8
Self-healing polymers, which can autonomously repair damage or be repaired through simple treatments, have garnered attention due to their flexibility in addressing damage and enabling long-term use in soft robotics. Many studies on the application of self-healing polymers to soft robotics have focused on realizing healable systems. Such a mechanism makes it possible to construct soft robots. Desp...Show More
DEFORM: Adaptive Formation Reconfiguration of Multi-Robot Systems in Confined Environments
Publication Year: 2025,Page(s):1 - 8
Achieving desired formation patterns without collisions is rather challenging for multi-robot systems in unknown obstacle-rich and confined environments, especially in narrow corridor scenes containing large-volume obstacles. To address this, we propose an adaptive formation reconfiguration method that can dynamically switch to the optimal formation pattern based on the current obstacle distributi...Show More
Multi-Contact Inertial Parameters Estimation and Localization in Legged Robots
Publication Year: 2025,Page(s):1 - 8
Optimal estimation is a promising tool for estimation of payloads' inertial parameters and localization of robots in the presence of multiple contacts. To harness its advantages in robotics, it is crucial to solve these large and challenging optimization problems efficiently. To tackle this, we (i) develop a multiple shooting solver that exploits both temporal and parametric structures through a p...Show More
Complete Coverage Path Planning Algorithm Based on Improved Biologically Inspired Neural Networks in Spray Painting
Lintao Huo;Ying Liu;Zengtao Chen;Yutu Yang;Xiaoan Yan;Haifei Xia;Qi Sun
Publication Year: 2024,Page(s):1 - 8
Intelligent putty coating technology is the main way to improve the degree of automation of railroad vehicle painting workshops. The two-component putty, which is currently used in the vehicle coating system, has extremely low fluidity, which requires improving the full coverage of the spray path while minimizing the number of gun switches, i.e., reducing the path overlap rate. We propose the foll...Show More
A Real-Time, Semi-Autonomous Navigation Platform for Soft Robotic Bronchoscopy
Daniel Van Lewen;Yitong Lu;Frank Juliá-Wise;Armaan Vasowalla;Christopher Wu;Jennifer Yeo;Ehab Billatos;Sheila Russo
Publication Year: 2025,Page(s):1 - 8
Navigating through the peripheral lung branches poses a significant challenge in diagnosing lesions during bronchoscopy. Soft robots are well-suited to address current limitations in bronchoscopy due to their scale, dexterity, and adaptability. In this paper, we propose a real-time, semi-autonomous navigation platform that leverages a soft continuum robot with an outer diameter of 2.5 mm for tip s...Show More
Design and Validation of a Non-Contact Bed MicroMovement Sensing System for HRV Monitoring
Publication Year: 2025,Page(s):1 - 8
The growing demand for non-wearable, long-term health monitoring solutions, especially for elderly, has driven the development of bed-based physiological monitoring systems. This letter introduces a novel non-contact, bed-based micromovement sensing system designed for accurate heart rate variability (HRV) monitoring. The system uses a polyvinylidene fluoride (PVDF) piezoelectric film sensor to de...Show More
Learning to Remove Bad Weather: Towards Robust Visual Perception for Self-Driving
Publication Year: 2022,Page(s):1 - 1
Cited by: Papers (4)
Visual perception plays a vital role in generating the intelligent actions of autonomous vehicles. However, various bad weather degradations can create visibility problems that impair the performance of high-level tasks. Though image enhancement techniques have been extensively studied for safe self-driving in bad weather, few studies have dealt with both enhancement and perception simultaneously....Show More
Virtual Masses Description Forming Conservative System for Periodic Trajectory Modification of Robust Intermittent Controller
Publication Year: 2025,Page(s):1 - 8
An intermittent controller, which alternates between phases of no control and feedback control, provides a robust, computationally and energetically efficient method by leveraging the robot's passive dynamics. However, this approach, especially during rapid motions and when facing disturbances, becomes unstable due to model errors during the single support phase; this is the no-control phase. This...Show More
MuSCLe-Reg: Multi-Scale Contextual Embedding and Local Correspondence Rectification for Robust Two-Stage Point Cloud Registration
Yangyang Zhang;Jialong Zhang;Xiaolong Qian;Yi Cen;Bowen Zhang;Jun Gong
Publication Year: 2025,Page(s):1 - 8
Algorithm of outlier removal for learning-based 3D point cloud registration is usually regarded as a classification problem. The core for this to be successful is to learn the discriminative inlier/outlier feature representations. This paper proposes a two-stage efficient network (MuSCLe-Reg) with multi-scale local feature fusion embedding. Specifically, we have designed a two-stage registration a...Show More
What's the Deal with Robot Comedy? Pinpointing the Impact of Post-Joke Repartee in a Robotic Comedian's Performance
Ayan Robinson;Sarah Woods;Madison R. Shippy;DeAndre Walcott;Naomi T. Fitter
Publication Year: 2025,Page(s):1 - 8
The rise in prevalence of AI-enabled technologies (from voice assistants to social robots) has not yet been accompanied by an analogous mastery of computer-mediated humor. Although humans often use jokes to repair interactions and navigate uncomfortable scenarios, social robots in similar roles typically fall short at reading the room and adapting behavior according to sensed social contexts and r...Show More
Trajectory Planning and Control for Robotic Manipulation of Magnetic Capsules
Publication Year: 2025,Page(s):1 - 8
Robotic magnetic manipulation offers a minimally invasive approach to gastrointestinal examinations through capsule endoscopy. However, controlling such systems using external permanent magnets (EPM) is challenging due to nonlinear magnetic interactions, especially when there are complex navigation requirements such as avoidance of sensitive tissues. In this work, we present a novel trajectory pla...Show More
Optimizing Plastic Waste Collection in Water Bodies Using Heterogeneous Autonomous Surface Vehicles with Deep Reinforcement Learning
Alejandro Mendoza Barrionuevo;Samuel Yanes Luis;Daniel Gutiérrez Reina;Sergio L. Toral Marín
Publication Year: 2025,Page(s):1 - 8
This paper presents a model-free deep reinforcement learning framework for informative path planning with heterogeneous fleets of autonomous surface vehicles to locate and collect plastic waste. The system employs two teams of vehicles: scouts and cleaners. Coordination between these teams is achieved through a deep reinforcement approach, allowing agents to learn strategies to maximize cleaning e...Show More
SOUS VIDE: Cooking Visual Drone Navigation Policies in a Gaussian Splatting Vacuum
JunEn Low;Maximilian Adang;Javier Yu;Keiko Nagami;Mac Schwager
Publication Year: 2025,Page(s):1 - 8
We propose a new simulator, training approach, and policy architecture, collectively called SOUS VIDE, for end-to-end visual drone navigation. Our trained policies exhibit zero-shot sim-to-real transfer with robust real-world performance using only onboard perception and computation. Our simulator, called FiGS, couples a computationally simple drone dynamics model with a high visual fidelity Gauss...Show More
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