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检索条件"机构=Robotics Engineering Program"

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Development of a Mixed-Reality Dual-User Training System for Robot Laparoscopic Surgery

Development of a Mixed-Reality Dual-User Training System for...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Chen, Ting-You Young, Kuu-Young Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Department of Electrical Engineering Hsinchu Taiwan

ISBN: (纸本)9781665410205

As robot surgery becomes more popular these days, it consequently solicits a high demand on its training system. Currently, most of the systems are intended for personal training, while it may be more effective if an experienced expert can also be involved. It thus motivates us to propose a dual-user robotic surgical training system that can closely link the mentor and trainee together. The system is developed in a mixed-reality environment that integrates the information from both the virtual and real worlds. The haptic feedback and virtual fixtures are employed for assistance during skill transfer. The proposed system can assess the proficiency level of the trainee for the mentor to provide proper assistance during training. The experimental results demonstrate that the proposed system is capable of enhancing the trainee's ability for surgery. Especially, similar effectiveness is observed during comparative studies with direct hands-on guidance frequently adopted for skill transfer during sport training. © 2024 IEEE.

关键词： Robotic surgery

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Designing an End-to-End UAV System for Insulator Inspection Under Transmission Tower Environments

Designing an End-to-End UAV System for Insulator Inspection ...

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2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

作者： Jeong, Jinyeong Park, Seongsu Lee, Sanghoon Youn, Donghyeon Kim, Min Jun School of Electrical Engineering KAIST Daejeon Korea Republic of KAIST Robotics Program Daejeon Korea Republic of KEPCO Research Institute Korea Electric Power Corporation Daejeon Korea Republic of

ISBN: (纸本)9798350371888

This paper proposes an unmanned aerial vehicle (UAV) equipped with a rigid contact module and two supplementary forward-direction motors, designed for the contact-based inspection of porcelain insulators. During the free-flight, this aerial robot is controlled by a geometric tracking controller. When approaching and contacting the insulators, the impedance controller generates enough force to sustain contact by using two forward-direction motors, while the geometric tracking controller maintains its orientation. This platform is validated through simulations, demonstrating its effectiveness in performing contact-based inspection tasks. © 2024 IEEE.

关键词： Inspection

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A Machine Learning-Based Routing Technique for Off-chain Transactions in Payment Channel Networks 5

A Machine Learning-Based Routing Technique for Off-chain Tra...

引用

5th IEEE International Conference on Smart Internet of Things, SmartIoT 2021

作者： Kadry, Heba Gadallah, Yasser Robotics Control and Smart Systems Program American University in Cairo New Cairo11835 Egypt Department of Electronics and Communications Engineering American University in Cairo New Cairo11835 Egypt

ISBN: (纸本)9781665445115

Blockchain is a foundational technology that has the potential to create new prospects for our economic and social systems. However, the lack of scalability limits the capability to deliver a target throughput and latency compared to the traditional financial systems. Layer-two is a collective term for solutions designed to enhance scalability by handling transactions off the main chain. For example, bidirectional payment channels allow the execution of fast transactions between two parties, thus forming the so-called payment channel networks (PCNs). Therefore, efficient routing protocols are needed to find a payment path from the sender to the receiver, with the lowest transaction fees. These protocols have to consider, among other factors, the unexpected online/offline behavior of the constituent payment nodes and the payment channel imbalance. This study proposes a novel machine learning-based technique for off-chain transaction routing. It is a fully distributed approach to be used within PCNs. For this purpose, the effect of the offline nodes and channel imbalance on the payment channels network are modeled. The simulation results demonstrate that the proposed technique strikes a good balance when considering the success ratio, transaction fees, routing efficiency, transaction overhead, and transaction maintenance overhead compared to other techniques that have previously been proposed for the same purpose. © 2021 IEEE.

关键词： Scalability

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A comparison of two algorithms for robot learning from demonstration

A comparison of two algorithms for robot learning from demon...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Halit Bener Suay Sonia Chernova Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA

Robot learning from demonstration focuses on algorithms that enable a robot to learn a policy from demonstrations performed by a teacher, typically a human expert. This paper presents an experimental evaluation of two learning from demonstration algorithms, Interactive Reinforcement Learning and Behavior Networks. We evaluate the performance of these algorithms using a humanoid robot and discuss the relative advantages and drawbacks of these methods with respect to learning time, number of demonstrations, ease of implementation and other metrics. Our results show that Behavior Networks rely on a greater degree of domain knowledge and programmer expertise, requiring very precise definitions for behavior pre- and post-conditions. By contrast Interactive RL requires a relatively simple implementation based only on the robot's sensor data and actions. However, Behavior Networks leverage the pre-coded knowledge to effectively reduce learning time and the required number of human interactions to learn the task.

关键词： Robot sensing systems Humans Strontium Learning Actuators Knowledge engineering

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Machine Learning Algorithms for Natural Language Processing Tasks: A Case of COVID-19 Twitter data (Thailand)

Machine Learning Algorithms for Natural Language Processing ...

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2022 International Conference on Computational Science and Computational Intelligence, CSCI 2022

作者： Kularbphettong, Kunyanuth Vichivanives, Rujijan Kanjanaprakarn, Pannawat Chutrtong, Jaruwan Ruksuntorn, Nareenart Suan Sunandha Rajabhat University Computer Science Program Bangkok Thailand Suan Sunandha Rajabhat University Faculty of Science and Technology Bangkok Thailand Suan Sunandha Rajabhat University Robotics Engineering Program Faculty of Industrial Technology Bangkok Thailand

ISBN: (纸本)9798350320282

This paper presents the use of natural language processing for the problem of information extraction and sentiment analysis. The dataset is from Twitter that has the information of people mentioning about COVID-19, this study has two tasks: (i) classification approach for information extraction task and (ii) deep learning approach for sentiment analysis task. In information extraction task, the data was gathered from twitter that related to COVID-19 information, and the sequence labelling method applied to classify text before giving it to classification algorithms (K-NN, Naïve Bayes, Decision Tree, Random Forest, and SVM). In sentiment analysis task, data was classified by convert the word into index and using word embedding, then to process deep learning algorithm (Bi-directional GRU). The accuracy of two tasks are 98% and 79% respectively. © 2022 IEEE.

关键词： COVID-19

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Topological Approximate Dynamic programming under Temporal Logic Constraints

Topological Approximate Dynamic Programming under Temporal L...

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IEEE Annual Conference on Decision and Control

作者： Lening Li Jie Fu Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

In this paper, we develop a model-free approximate dynamic programming method for stochastic systems modeled as Markov decision processes to maximize the probability of satisfying high-level system specifications expressed in a subclass of temporal logic formulas-syntactically co-safe linear temporal logic. Our proposed method includes two steps: First, we decompose the planning problem into a sequence of sub-problems based on the topological property of the task automaton which is translated from a temporal logic formula. Second, we extend a model-free approximate dynamic programming method to solve value functions, one for each state in the task automaton, in an order reverse to the causal dependency. Particularly, we show that the run-time of the proposed algorithm does not grow exponentially with the size of specifications. The correctness and efficiency of the algorithm are demonstrated using a robotic motion planning example.

关键词： Task analysis Planning Dynamic programming Markov processes Automata Approximation algorithms Function approximation

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Efficient color feature extraction and matching for motion estimation and mapping

Efficient color feature extraction and matching for motion e...

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2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

作者： Hwang, Hyoseok Kweon, In-So Robotics Program Korea Advanced Institute of Science and Technology Daejon Korea Republic of Faculty of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejon Korea Republic of

ISBN: (纸本)9781424420582

Feature extraction and matching is one of the most significant research areas in robot vision. In this paper, we present a new method for motion estimation and mapping using color feature extraction and matching. The proposed method reduces computational cost and has good performance. The experimental result shows that the proposed method not only runs faster but provides accurate result.

关键词： Motion estimation

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Sampling-based approximate optimal temporal logic planning

Sampling-based approximate optimal temporal logic planning

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IEEE International Conference on robotics and Automation (ICRA)

作者： Lening Li Jie Fu Robotics Engineering Program Worcester Polytechnic Institute Worcester MA US

In this paper, we propose a sampling-based policy iteration for optimal planning under temporal logic constraints. The method integrates approximate optimal control, importance sampling, and formal methods. For a subclass of linear temporal logic, the planning problem is transformed to an optimal control problem for a hybrid system where discrete transitions are triggered by linear time events in temporal logic. Instead of solving the Hamilton-Jacobi-Bellman equation, we use policy function approximation to reduce the problem into a search of an optimal weight vector that parametrizes the near-optimal policy for given bases. Then, we incorporate Model Reference Adaptive Search - an importance sampling-based optimization algorithm to perform a sample-efficient search within the parameter space of policy function approximations. Facing the discontinuity in cost function introduced by temporal logic constraints and system dynamics, we introduce (1) a rank function in formal logic specifications to enable sample-efficient search; (2) specification-guided basis selection. Under mild technical assumptions, the proposed algorithm converges, with probability one, to a global approximate optimal policy that ensures the satisfaction of temporal logic constraints. The correctness and efficiency of the method are demonstrated through numerical experiments including temporal logic planning for a linear system and a nonlinear mobile robot.

关键词： Planning Approximation algorithms Trajectory Function approximation Nonlinear systems Optimal control Automata

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Design of a High-level Teleoperation Interface Resilient to the Effects of Unreliable Robot Autonomy

Design of a High-level Teleoperation Interface Resilient to ...

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2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Samuel S. White Keion W. Bisland Michael C. Collins Zhi Li Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

High-level control is generally preferred for the control of complex robot platforms and by users inexperienced with robot teleoperation. However, high-level teleoperation interfaces can be less effective if the robot autonomy is not reliable. To address this problem, it is important to understand how the users' preference of teleoperation interface may vary with the reliability of the robot autonomy, and understand what design features ameliorate the frustration and effort caused by unreliable *** paper proposes a graphical user interface for high-level robot control. The framework of the interface enables teleoperators to control a robot at the action level, and incorporates a simple but effective design that enables teleoperators to recover from task failure in a number of ways. We conducted a user study (N = 25) to compare the performance and user experience when using the proposed high-level interface to a low-level interface (i.e., gamepad) for robot low-level control, on a representative manipulation task. We also investigated if the high-level teleoperation interface remains effective if the reliability of robot autonomy decreases. Our results show that a high-level interface able to handle the most frequent errors is resilient to the effects of unreliable robot autonomy. Although the total task completion time increased as the robot autonomy becomes unreliable, the users' perception of workload and task performance are not affected. Through the user study, we also reveal the desirable interface features.

关键词： Teleoperators Robot control Reliability engineering User experience Task analysis Robots Graphical user interfaces

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Novel EOD robot design with dexterous gripper and intuitive teleoperation

Novel EOD robot design with dexterous gripper and intuitive ...

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Proceedings of the Biannual World Automation Congress

作者： Matthew W. Carey Eric M. Kurz Joshua D. Matte Timothy D. Perrault Taskin Padir Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA

This paper details the design and implementation of an intelligent explosive ordnance disposal robot to provide law enforcement agencies with a cost effective and reliable robotic platform. The key features of the robot include an intuitive user interface which provides additional sensor feedback and enhanced visual awareness compared to existing systems, an on-board three degree of freedom manipulator arm providing an enlarged workspace, and a dexterous gripper allowing for the removal of blasting caps. The flexible and modular robot design utilizes commercial off-the-shelf components for ease of maintenance and repairs. The robot provides a safe distance threat assessment and increased capacity for explosive ordnance disposal, improving the effectiveness of bomb disposal teams. The robot's low-cost, intuitive operation and ease-of-maintenance promote its widespread appeal, thereby saving the lives of both law enforcement personnel and civilians.

关键词： Grippers Robot kinematics Cameras Explosives Robot vision systems

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