Article
Automation & Control Systems
Yong You, Jingtao Wu, Yunlong Meng, Dongye Sun, Datong Qin
Summary: A new power-cycling variable transmission (PCVT) is proposed and applied to construction vehicles to improve transmission efficiency. A shift correction strategy is developed based on identifying the changes in construction vehicles' mass and gradient. Simulation results show that the proposed method can correct shift points, improve operation efficiency, and ensure a safer operation process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pedro Azevedo, Vitor Santos
Summary: Accurate detection and tracking of vulnerable road users and traffic objects are vital tasks for autonomous driving and driving assistance systems. This paper proposes a solution for object detection and tracking in an autonomous driving scenario, comparing different object detectors and exploring the deployment on edge devices. The effectiveness of DeepStream technology and different object trackers is assessed using the KITTI tracking dataset.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Benjamin Beiter, Divya Srinivasan, Alexander Leonessa
Summary: Powered exoskeletons can significantly reduce physical workload and have great potential impact on future labor practices. To truly assist users in achieving task goals, a shared autonomy control framework is proposed to separate the control objectives of the human and exoskeleton. Positive Power control is introduced for the human-based controller, while 'acceptance' is used as a measure of matching the exoskeleton's control objective to the human's. Both control objectives are implemented in an optimization-based Whole-Body-Control structure. The results verify the effectiveness of the control framework and its potential for improving cooperative control for powered exoskeletons.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shota Kokubu, Pablo E. Tortos Vinocour, Wenwei Yu
Summary: In this study, a new modular soft actuator was proposed to improve the support performance of soft rehabilitation gloves (SRGs). Objective evaluations and clinical tests were conducted to demonstrate the effectiveness and functionality of the proposed actuator and SRG.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Runwei Guan, Shanliang Yao, Lulu Liu, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee, Yutao Yue
Summary: With the development of Unmanned Surface Vehicles (USVs), the perception of inland waterways has become significant. Traditional RGB cameras cannot work effectively in adverse weather and at night, which has led to the emergence of 4D millimeter-wave radar as a new perception sensor. However, the radar suffers from water-surface clutter and irregular shape of point cloud. To address these issues, this paper proposes a high-performance panoptic perception model called Mask-VRDet, which fuses features of vision and radar using graph neural network.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Gabriele Abbate, Alessandro Giusti, Viktor Schmuck, Oya Celiktutan, Antonio Paolillo
Summary: In this study, a learning-based approach is proposed to predict the probability of human users interacting with a robot before the interaction begins. By considering the pose and motion of the user, the approach labels the robot's encounters with humans in a self-supervised manner. The method is validated and deployed in various scenarios, achieving high accuracy in predicting user intentions to interact with the robot.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pengchao Ding, Faben Zhu, Hongbiao Zhu, Gongcheng Wang, Hua Bai, Han Wang, Dongmei Wu, Zhijiang Du, Weidong Wang
Summary: We propose an autonomous approaching scheme for mobile robot traversing obstacle stairwells, which overcomes the restricted field of vision caused by obstacles. The scheme includes stair localization, structural parameter estimation, and optimization of the approaching process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shaorui Liu, Wei Tian, Jianxin Shen, Bo Li, Pengcheng Li
Summary: This paper proposes a two-objective optimization technique for multi-robot systems, addressing the issue of balancing productivity and machining performance in high-quality machining tasks.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Tiago Cortinhal, Eren Erdal Aksoy
Summary: This work presents a new depth-and semantics-aware conditional generative model, named TITAN-Next, for cross-domain image-to-image translation between LiDAR and camera sensors. The model is able to translate raw LiDAR point clouds to RGB-D camera images by solely relying on semantic scene segments, and it has practical applications in fields like autonomous vehicles.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Engineering, Multidisciplinary
Qiang Zou, Chengdong Wu, Ming Cong, Dong Liu
Summary: This paper proposes a cognitive map-based hierarchical navigation method to improve the robot's autonomous navigation ability. The method draws inspiration from mammal's navigation, mapping perceptual information into cognitive space and exhibiting strong autonomy and environment adaptability. Experimental results demonstrate that the proposed path planning method can efficiently avoid obstacles and find the preferred global path to the target, while the motion controlling results reflect strong bionic properties.
JOURNAL OF BIONIC ENGINEERING
(2023)
Article
Instruments & Instrumentation
Shinsuke Oh-hara, Atsushi Fujimori
Summary: This paper presents a leader-follower formation control of multiple mobile robots using a fisheye camera. The camera is first modeled on spherical coordinates and a position estimation technique is proposed based on an AR marker. The velocity of the leader robot is estimated using a disturbance observer. The proposed techniques are combined with a formation control based on a virtual structure, and the stability of the total system is analyzed using Lyapunov theorem.
Article
Robotics
Heqiu Song, Konstantinos Tsiakas, Jaap Ham, Panos Markopoulos, Emilia I. Barakova
Summary: This research examines how designing social robots for piano practice can enhance self-regulated learning skills. The experiment conducted in a music school with 50 children showed that when children interacted with a self-assessment robot, they had higher motivation and better performance compared to when they interacted with a non-evaluative robot. Interactions among the robot conditions, children's learning stages, and gender also influenced motivation and rhythm performance.
INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS
(2023)
Article
Robotics
Seongcheol Kim, Casey C. Bennett, Zachary Henkel, Jinjae Lee, Cedomir Stanojevic, Kenna Baugus, Cindy L. Bethel, Jennifer A. Piatt, Selma Sabanovic
Summary: This paper presents a study on human-specific behavior classification based on data collected through EMA and sensors attached onboard a SAR. Classification was conducted using generative replay models, and both multi-class and binary classification were explored. The results showed higher accuracy in binary classification compared to multi-class classification.
INTELLIGENT SERVICE ROBOTICS
(2023)
Article
Robotics
Placido Falqueto, Alessandro Antonucci, Luigi Palopoli, Daniele Fontanelli
Summary: Robot-assisted navigation requires flexible control approaches. Shared authority control is proposed to determine the level of authority given to humans. This paper presents a new paradigm combining machine learning and adaptive control to evaluate the correctness of human behavior in real-time. Experimental results demonstrate the feasibility of this approach.
INTELLIGENT SERVICE ROBOTICS
(2023)
Article
Robotics
Pian Yu, Yulong Gao, Frank J. Jiang, Karl H. Johansson, Dimos V. Dimarogonas
Summary: This paper studies the online control synthesis problem for uncertain discrete-time systems subject to signal temporal logic (STL) specifications. The authors propose an approach based on STL, reachability analysis, and temporal logic trees. They demonstrate the effectiveness of the approach through simulation examples and a hardware experiment.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2023)
Article
Instruments & Instrumentation
Toshio Takayama, Masaki Waragai
Summary: Electric motors are widely used globally, but achieving high energy efficiency remains a challenge. This paper proposes a coupled-driven switchable transmission system for robots, which can switch between high-speed and high-torque drives using the output of two motors. Experimental results show that this device can be controlled using conventional voltage control.
Article
Instruments & Instrumentation
Tomohiro Komatsu, Keiji Nagatani, Yasuhisa Hirata
Summary: This paper describes the effect and challenges of applying the spiral model to the development of a robot system for a new entrant company. The spiral model's iterative and step-by-step approach successfully resulted in the development of a robust robot system, improving the safety of operators in disaster emergency restoration.
Article
Robotics
Bo-Yeon Lee, Seonggi Kim, Sunjong Oh, Youngoh Lee, Jonghwa Park, Hyunhyub Ko, Ja Choon Koo, Youngdo Jung, Hyuneui Lim
Summary: In this study, a real-time and multimodal tactile system was developed to mimic the function of human skin. The system is capable of acquiring different types of tactile information simultaneously and differentiating between various tactile stimuli, texture characteristics, and consecutive complex motions.
Article
Robotics
Haochen Shi, Huazhe Xu, Zhiao Huang, Yunzhu Li, Jiajun Wu
Summary: Modeling and manipulating elasto-plastic objects are crucial for robots to perform complex tasks. This paper proposes a particle-based representation combined with graph neural networks to tackle the challenges in representing states, modeling dynamics, and synthesizing control signals. The experiments show that with a short training time, the robot can learn to deform objects into various complex shapes.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2023)
Article
Robotics
Jianhua Li, Dingjia Li, Chongyang Wang, Wei Guo, Zhidong Wang, Zhongtao Zhang, Hao Liu
Summary: This study proposes a comprehensive control framework that allows multi-segment continuum robots to automatically avoid collision and self-collision while maintaining the surgeon's control over the end effector's movement. The framework implements the use of screw theory to detect collisions early and actively avoid them. The results of simulations and physical experiments demonstrate the feasibility and effectiveness of the proposed framework in minimizing collision risk.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2023)
