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Article
Engineering, Electrical & Electronic
Yuntao Xue et al.
Summary: This paper focuses on the use of deep reinforcement learning methods to enable safe navigation of UAVs in unknown large-scale environments. The perception-constrained navigation of UAV is modeled as a partially observable Markov decision process (POMDP), and a fast recurrent stochastic valued gradient algorithm based on the actor-critic framework is proposed for online solution. The proposed navigation method maps raw sensing information into navigation signals, allowing the UAV to navigate safely in unknown cluttered environments without real-time map building.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Automation & Control Systems
Lu Liu et al.
Summary: This article proposes a multi-underwater unmanned vehicle (UUV) maneuvering decision-making algorithm for a counter-game with a dynamic target scenario. The game is modeled with interval-valued intuitionistic fuzzy rules, and an optimal maneuvering strategy is realized using a fractional-order recurrent neural network (RNN). The underwater environments with weak connectivity, underwater noise, and dynamic uncertainties are analyzed and incorporated into the interval-valued intuitionistic fuzzy set. The effectiveness of the proposed algorithm is demonstrated through simulation and experimental results, and the influence of the fractional order on the convergence rate and optimization error is examined.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Information Systems
Qiuxiang Gu et al.
Summary: With the rapid development of the manufacturing industry, higher machining accuracy of parts is required for industrial automation equipment, especially computer numerical control (CNC) machine tools. The parallel platform solution, based on the Stewart six degrees of freedom parallel platform, is theoretically more suitable for high-precision machining equipment. This paper focuses on the construction of the parallel platform, including mechanical structure design, motor driver circuit design, and programming for controlling the parallel robotic arms and the platform control center. The closed-loop control effect of the parallel platform workspace pose is achieved.
Article
Automation & Control Systems
Fazhi Song et al.
Summary: This paper proposes a cross-coupling iterative learning control method for accurate pattern transfer in wafer scanners, which includes synchronization control of the reticle stage and the wafer stage, and improvement strategies such as adaptive gain and tuning of the learning filter. Experimental results demonstrate the high effectiveness and superiority of the proposed method.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Amylia Ait Saadi et al.
Summary: This paper provides an overview of UAV path planning approaches, which are classified into five main categories. A critical analysis is given for each category based on targets, constraints, and environments. Additionally, highlights and future research directions for UAV path planning are suggested.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2022)
Article
Engineering, Civil
Shengchuan Jiang et al.
Summary: This article proposes a three-stage layout planning approach for UWB base stations, which can meet the positioning accuracy requirements of automated valet parking system and ensure stability and economy.
JOURNAL OF ADVANCED TRANSPORTATION
(2022)
Article
Robotics
Reinis Cimurs et al.
Summary: This letter presents an autonomous navigation system for exploring unknown environments using deep reinforcement learning (DRL). The system selects optimal waypoints and learns a motion policy for local navigation to guide the robot towards a global goal. Experimental results show that the proposed method outperforms similar exploration methods in complex static and dynamic environments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Bin Li et al.
Summary: This paper studies the 3D trajectory optimization problem for UAV-aided wireless communication, proposing a control-based UAV trajectory design method and deriving a new energy consumption model.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Haoge Jiang et al.
Summary: This paper proposes a low-level motion controller based on deep reinforcement learning (DRL) for map-less autonomous navigation in dynamic scenes. It introduces three enhancements to the navigation task and outperforms conventional methods in several aspects, including not requiring prior knowledge of the environment and metric map, lower reliance on accurate sensors, learning emergent behavior in dynamic scenes, and the ability to transfer to real robots without further fine-tuning.
Article
Computer Science, Information Systems
Imran Mir et al.
Summary: This work provides an overview of effective communication techniques for space exploration using ground, aerial, and underwater vehicles. It comprehensively summarizes trajectory planning, space exploration, optimization, and other challenges faced, and presents potential directions for future research.
Article
Computer Science, Artificial Intelligence
Han Ma et al.
Summary: This article introduces a risk-based algorithm with a bidirectional search sampling strategy for efficient AGV navigation in human-AGV coexisting environments. The proposed algorithm bypasses the two-point boundary value problem and retains the advantages of the bidirectional search sampling strategy by using the other direction as a heuristic.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2022)
Article
Robotics
Lvbang Tang et al.
Summary: This paper presents a trajectory planning framework based on B-spline and kinodynamic search for autonomous navigation of quadrotor. The framework efficiently generates safe and reasonable flight trajectories, which are further optimized to improve trajectory smoothness and reduce control cost through solving a quadratically constrained quadratic programming problem. Extensive analysis and comparative simulation experiments validate the effectiveness of the proposed framework, which has been integrated into a vision-based quadrotor autonomous navigation system and verified through multiple outdoor flight experiments.
JOURNAL OF FIELD ROBOTICS
(2021)
Article
Computer Science, Artificial Intelligence
Qinghe Zheng et al.
Summary: In this paper, a two-level data augmentation method based on spectrum interference in deep learning is proposed for automatic modulation classification. Data augmentation at both training and testing stages can improve the generalization performance of deep neural network.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Bartomeu Rubi et al.
Summary: This paper proposes a deep reinforcement learning approach to solve the quadrotor path following and obstacle avoidance problem by using two agents. A novel structure is introduced to interpret training outcomes, achieve faster training, and ensure safety in real quadrotor training. The simulation results validate the effectiveness of the proposed method.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2021)
Article
Computer Science, Information Systems
Tuo Shi et al.
Summary: The Battery-Free Sensor Network (BF-WSN) is a new network architecture that overcomes energy limitations of traditional wireless sensor networks. The concept of Joint Deployment aims to maximize network coverage quality in BF-WSNs, proving to be an efficient and effective solution through extensive simulations.
ACM TRANSACTIONS ON SENSOR NETWORKS
(2021)
Article
Computer Science, Information Systems
Muhammad Atif et al.
Summary: In the aftermath of disasters, it is crucial to localize trapped victims for their safety and rescue. This article introduces a novel approach using unmanned aerial vehicles (UAVs) for localization and path planning, which can extract neighbor information from devices using directed wireless power transfer. The proposed method optimizes UAV search energy and reduces energy costs by clustering in noisy environments, achieving linear scaling of the searched area with noise levels.
IEEE SYSTEMS JOURNAL
(2021)
Proceedings Paper
Computer Science, Information Systems
Mengyu Chen et al.
Summary: The accelerated development of IoT has led to a high demand for data collection from WSNs, with UAVs considered a promising technology to improve efficiency. This paper focuses on improving data collection efficiency in WSNs using UAV trajectory finding, formulating a novel maximization problem and devising an efficient algorithm to address it. Simulation results show the proposed algorithm outperforms other heuristics significantly.
2021 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC)
(2021)
Proceedings Paper
Automation & Control Systems
Yiting Kang et al.
Summary: Various algorithms based on RRT methods are used for motion planning, with the novel reconnection method in Smooth-RRT* generating smooth curved trajectories and considering kinodynamic constraints. The algorithm outperforms both RRT* and Kino-RRT by providing shorter and smoother planned paths with fewer expansion nodes under the same time consumption, demonstrating its capability to satisfy kinodynamic constraints and ensure asymptotic optimality.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Yunlong Song et al.
Summary: This research introduces a new approach to near-time-optimal trajectory generation for quadrotors using deep reinforcement learning and relative gate observations. The method is capable of computing near-time-optimal trajectories and adapting to changes in the environment, showing computational advantages over traditional trajectory optimization methods. The approach is evaluated on race tracks in simulation and with a physical quadrotor, achieving speeds of up to 60 km/h.
2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2021)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Hanlin Niu et al.
Summary: This paper introduces a sensor-level mapless collision avoidance algorithm for mobile robots, which learns from both human and self-exploratory data through an efficient training strategy. Experimental results show that the algorithm performs well in two different environments.
2021 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII)
(2021)
Article
Computer Science, Information Systems
Chi Harold Liu et al.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2020)
Article
Computer Science, Information Systems
Lei Yang et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
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Chao Wang et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Article
Automation & Control Systems
Chao Yan et al.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2020)
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Mathematical & Computational Biology
Xiaoyong Xiong et al.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2020)
Article
Business
Nader Mohamed et al.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2020)
Article
Robotics
Peide Cai et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2020)
Article
Robotics
Hao-Tien Lewis Chiang et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2019)
Article
Transportation Science & Technology
Zhengyu Yao et al.
SAE INTERNATIONAL JOURNAL OF ALTERNATIVE POWERTRAINS
(2019)
Article
Robotics
Hao-Tien Lewis Chiang et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2019)
Article
Automation & Control Systems
Zhaowei Ma et al.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2018)
Article
Engineering, Electrical & Electronic
Kai Arulkumaran et al.
IEEE SIGNAL PROCESSING MAGAZINE
(2017)
Article
Robotics
Michael Otte et al.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2016)
Article
Automation & Control Systems
Chang-bae Moon et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2015)
Article
Multidisciplinary Sciences
Volodymyr Mnih et al.
Article
Engineering, Biomedical
Bo Jin et al.
BIO-MEDICAL MATERIALS AND ENGINEERING
(2014)
Article
Robotics
Sertac Karaman et al.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2011)