Publications

@article{LI2023105142,

title = {A systematic review on load carriage assistive devices: Mechanism design and performance evaluation},

author = {Tong Li and Qingguo Li},

url = {https://www.sciencedirect.com/science/article/pii/S0094114X22003883},

doi = {https://doi.org/10.1016/j.mechmachtheory.2022.105142},

issn = {0094-114X},

year  = {2023},

date = {2023-11-01},

urldate = {2023-01-01},

journal = {Mechanism and Machine Theory},

volume = {180},

pages = {105142},

abstract = {Manually carrying loads for a long distance and duration is highly physically demanding for humans but commonly required in outdoor activities. With the rapid growth and advancement of wearable robotics, many explorations have been conducted to design and evaluate robotic systems, aiming to enhance human capacity and/or endurance in load carriage tasks. In this paper, state-of-the-art robotic load carriage assistive devices are systematically reviewed regarding the mechanisms and their performances in experimental evaluation. Methods and strategies of assisting load carriage are analyzed and the existing devices are categorized into four classes: (1) reducing inertial force of the load, (2) transferring load weight to the ground, (3) assisting human joints, and (4) integration of transferring load weight and assisting human joints. The efficacy of different mechanism designs and assisting strategies are discussed from both engineering and biomechanical perspectives. Based on these analyses, challenges in the current studies and further efforts required in developing better assistive devices are discussed to provide insights for future studies.},

keywords = {Assistive device, Exoskeleton, Human power augmentation, Load carriage, Performance evaluation},

pubstate = {published},

tppubtype = {article}

}

@article{CHAWLA2023105107,

title = {Inverse and Forward Kineto-Static Solution of a Large-Scale Cable-Driven Parallel Robot using Neural Networks},

author = {Ishan Chawla and P.  M. Pathak and Leila Notash and A.  K. Samantaray and Qingguo Li and U.  K. Sharma},

url = {https://www.sciencedirect.com/science/article/pii/S0094114X22003536},

doi = {https://doi.org/10.1016/j.mechmachtheory.2022.105107},

issn = {0094-114X},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Mechanism and Machine Theory},

volume = {179},

pages = {105107},

abstract = {This kineto-static problem of cable-driven parallel robot (CDPR) considering cable mass and elasticity is a highly non-linear and computationally complex problem. Numerical methods are conventionally employed to solve this problem. However, numerical methods are highly dependent on initial values, iterative in nature, computationally unbounded, and have slow convergence speed, making them unreliable for real-time scenarios. Therefore, this paper proposes a neural network-based approach to obtain the inverse kineto-static (IKS) as well as the forward kineto-static (FKS) solution of CDPR with significant cable mass and elasticity. The simulation results are presented for two cases, i.e., for a redundantly constrained planar CDPR (RP-CDPR) and a minimally constrained spatial CDPR (MS-CDPR). The training time, dataset requirement and testing error is observed to be significantly lower for MS-CDPR in comparison to RP-CDPR. For both the cases, the proposed approach shows a significant improvement in the computational speed when compared to numerical methods for both IKS and FKS problem. Owing to the advantage of bounded and low computational time, the proposed neural network-based approach is recommended for use in real-time applications.},

keywords = {Cable-Driven Parallel Robot, Forward Kineto-Static, Inverse Kineto-Static, Neural network, Sagging Cables},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1080/00140139.2022.2150322,

title = {Multi-phase optimisation model predicts manual lifting motions with less reliance on experiment-based posture data},

author = {Size Zheng and Qingguo Li and Tao Liu},

url = {https://doi.org/10.1080/00140139.2022.2150322},

doi = {10.1080/00140139.2022.2150322},

year  = {2022},

date = {2022-11-16},

urldate = {2022-01-01},

journal = {Ergonomics},

volume = {0},

number = {0},

pages = {1-16},

publisher = {Taylor & Francis},

abstract = {Optimisation-based predictive models are widely-used to explore the lifting strategies. Existing models incorporated empirical subject-specific posture constraints to improve the prediction accuracy. However, over-reliance on these constraints limits the application of predictive models. This paper proposed a multi-phase optimisation method (MPOM) for two-dimensional sagittally symmetric semi-squat lifting prediction, which decomposes the complete lifting task into three phases—the initial posture, the final posture, and the dynamic lifting phase. The first two phases are predicted with force- and stability-related strategies, and the last phase is predicted with a smoothing-related objective. Box-lifting motions of different box initial heights were collected for validation. The results show that MPOM has better or similar accuracy than the traditional single-phase optimisation (SPOM) of minimum muscular utilisation ratio, and MPOM reduces the reliance on experimental data. MPOM offers the opportunity to improve accuracy at the expense of efforts to determine appropriate weightings in the posture prediction phases. },

note = {PMID: 36398736},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1061/(ASCE)BE.1943-5592.0001971,

title = {Field Test of a Shear Force Measurement Technique Using Fiber Optic Sensing under Variable Speed Truck Loading},

author = {Jack Gillham and Neil A. Hoult and Evan C. Bentz},

url = {https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29BE.1943-5592.0001971},

doi = {10.1061/(ASCE)BE.1943-5592.0001971},

year  = {2022},

date = {2022-11-01},

urldate = {2022-01-01},

journal = {Journal of Bridge Engineering},

volume = {27},

number = {12},

pages = {04022115},

abstract = {The measurement of reaction forces at bridge bearings would enable engineers tasked with maintaining bridges to detect potential damage to the bearing and bridge by detecting changes in the load distribution at the supports with time. Currently, measuring the load in the bearing requires sensors built into the bearing, which means that they are hard to repair when damaged and cannot be installed after the bridge is built (unless the bearings are replaced). A potential alternative is the use of distributed fiber optic sensors (DFOS) that could be used to measure curvature in the beams of a bridge, which can then be used to calculate the moment, shear, and ultimately reaction force due to live loading. To investigate this, a DFOS system was installed on a newly built steel girder bridge on a single beam near one of the piers. A series of load tests were undertaken using a truck with a known load and driving along the bridge directly over the instrumented beam at speeds ranging from pseudo-static up to 30 km/h. The maximum measured strain in the bridge beam was 15 microstrain, which was lower than can be measured with certain DFOS systems, and highlighted the need to select a system with appropriate accuracy and precision. The measured strains were used to calculate the beam shear at the pier as the truck moved across the bridge. These results were compared with a continuous beam and two grillage analyses, and it was found that, based on the continuous beam model, about 25% of the total truck load was being carried by the beam, which was lower than the code live load distribution factor suggested. The grillage models provided better estimates of load spreading but were still conservative and dependent on the choice of transverse stiffness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9915368,

title = {FRUIT: A Blockchain-based Efficient and Privacy-preserving Quality-aware Incentive Scheme},

author = {Chuan Zhang and Mingyang Zhao and Liehuang Zhu and Weiting Zhang and Tong Wu and Jianbing Ni},

url = {https://ieeexplore.ieee.org/abstract/document/9915368},

doi = {10.1109/JSAC.2022.3213341},

issn = {1558-0008},

year  = {2022},

date = {2022-11-01},

urldate = {2022-11-01},

journal = {IEEE Journal on Selected Areas in Communications},

pages = {1-1},

abstract = {Incentive plays an important role in knowledge discovery, as it impels users to provide high-quality knowledge. To promise incentive schemes with transparency, blockchain technology has been widely used in incentive schemes. Currently, privacy, reliability, streamlined processing, and quality awareness are major challenges in designing blockchain-based incentive schemes. In this paper, we design a blockchain-based eFficient and pRivacy-preserving qUality-aware IncenTive scheme called FRUIT. With well-designed smart contracts, FRUIT achieves privacy, reliability, streamlined processing, and quality awareness during the whole procedure. Specifically, we design a novel lightweight encryption method by combining matrix decomposition with proxy re-encryption and a privacy-preserving task allocation based on the polynomial fitting function and hash function. Then, we leverage our proposed lightweight encryption and task allocation to build an efficient and privacy-preserving knowledge discovery protocol in order to securely calculate the data quality and truthful knowledge. To promise user reliability in the incentive scheme, we utilize the Dirichlet distribution to realize the automatic reputation prediction based on the data quality by deploying the reputation management on the blockchain. Moreover, we also deploy the payment management on the blockchain, endowing the incentive scheme to reward participants based on the data quality automatically. Through a detailed security analysis, we demonstrate that data privacy and task privacy are well preserved during the whole process. Theoretical analysis and extensive experiments on real-world datasets demonstrate that FRUIT has acceptable efficiency and affordable performance in terms of computation cost, communication overhead, and gas consumption.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hungler_Chabot_Mirzoian_Moozeh_2022,

title = {Virtual Reality Broken Plant Tutorial for Capstone Design},

author = {Paul Hungler and Michael Chabot and Lev Mirzoian and Kimia Moozeh},

url = {https://ojs.library.queensu.ca/index.php/PCEEA/article/view/15949},

year  = {2022},

date = {2022-11-01},

urldate = {2022-11-01},

journal = {Proceedings of the Canadian Engineering Education Association (CEEA)},

abstract = {Providing student capstone teams with an opportunity to demonstrate their design competency and complete a team challenge inside a full-scale chemical processing plant provides a novel learning opportunity. A full-scale virtual reality (VR) chemical processing plant was built as an immersive learning application for the Chemical Engineering and Engineering Chemistry capstone design course at Queen’s University in Kingston. During their capstone design course, student teams are required to work on the design of an ampicillin processing facility and the VR application was designed to provide a high-fidelity representation of an operating plant, including a piping and instrumentation diagram (P&ID). To examine the impact of this new VR learning tool, a broken plant exercise was designed to examine the efficacy of the application. The student cohort was divided into two groups for the exercise; paper-based, and web VR based. Each group completed several surveys and a tutorial problem. Initial quantitative results comparing the survey responses from both groups will be presented.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hungler_Thurgood_Marinova_White_Mirzoian_Thoms_Law_Chabot_Moozeh_2022,

title = {Design and Development of an Open-Source Virtual Reality Chemical Processing Plant},

author = {Paul Hungler and Chris Thurgood and Mariya Marinova and Steve White and Lev Mirzoian and Matthew Thoms and Janice Law and Michael Chabot and Kimia Moozeh},

url = {https://ojs.library.queensu.ca/index.php/PCEEA/article/view/15939},

year  = {2022},

date = {2022-11-01},

urldate = {2022-11-01},

journal = {Proceedings of the Canadian Engineering Education Association (CEEA)},

abstract = {It is challenging to provide students studying in chemical engineering, biotechnology and other related fields with an opportunity to tour and interact with a full-scale chemical processing plant. To address this challenge, an open-sourced virtual reality (VR) chemical processing plant was designed and built to provide students with an experiential learning opportunity. The VR plant is modelled after an ampicillin processing facility complete with a piping and instrumentation diagram (P&ID). The initial student experience inside the VR plant is a tour of the plant, various plant features and unit operations. The tour enables students to freely tour the plant but also engages them in a “Quest” style experience where they need to search for specific areas and components within the plant. An EngPad was designed to provide learners with a help tool to assist their navigation and strengthen their understanding during the VR experience. Experiential learning theory was used to guide the design of the VR application and take students through the four learning modes of concrete experience, reflective observation, abstract conceptualization, and active experimentation. A focus group provided feedback on the design and user interaction of the VR experience. This paper will outline how design features and enhancements were selected based on their connection to experiential learning theory.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9931405,

title = {Flocks, Mobs, and Figure Eights: Swarming as a Lemniscatic Arch},

author = {Peter T. Jardine and Sidney Givigi},

url = {https://ieeexplore.ieee.org/abstract/document/9931405},

doi = {10.1109/TNSE.2022.3217460},

issn = {2327-4697},

year  = {2022},

date = {2022-10-27},

urldate = {2022-01-01},

journal = {IEEE Transactions on Network Science and Engineering},

pages = {1-12},

abstract = {Inspired by the natural mobbing behavior of birds, this work presents a novel, quasi-distributed swarming strategy called the Dynamic Lemniscatic Arch. It resolves the problem of producing globally-stable, evenly-spaced lemniscate (or, figure-eight) trajectories while relying on local interactions only. Such trajectories are advantageous in applications where energy consumption and mechanical strain must be minimized. Previous work in lemniscate curves has typically relied on predetermined trajectories, rather than on the emergent structure of the swarm. Furthermore, we enrich the traditional 2-dimensional lemniscate plane curve structure by forming an arch in the third dimension. This arch provides more consistent coverage in surveillance type tasks and, with minor variations in parameters, can be used to produce mobbing behavior. The technique relies on time-varying quaternion rotations linked to the positions of dynamically induced virtual agents. We provide a mathematical proof of stability, which demonstrates the swarm converges to the desired geometry. Simulations show that the strategy performs well with multiple agents and in numerous different configurations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RAZI2022102897,

title = {Coupled stability analysis of cascaded leader–follower teleoperation networks using Möbius transformation},

author = {Kamran Razi and Chiedu N. Mokogwu and Keyvan Hashtrudi-Zaad},

url = {https://www.sciencedirect.com/science/article/pii/S0957415822001155},

doi = {https://doi.org/10.1016/j.mechatronics.2022.102897},

issn = {0957-4158},

year  = {2022},

date = {2022-10-01},

urldate = {2022-10-01},

journal = {Mechatronics},

volume = {88},

pages = {102897},

abstract = {In this paper, we use the notion of Möbius transformation to develop a chain-wise methodology for the analysis of coupled stability in a cascade of leader–follower networks. The methodology tracks the transmission of the load passivity unit disk through the cascade to the user network. It allows for networks in the cascade that are neither passive nor absolutely stable. Due to its modularity, the proposed methodology is more suitable for dynamic distributed systems in which a network block, such as virtual coupling or delay in the cascade, is modified, added or taken out. We also introduce the notion of “bounded-Γ absolute stability” to verify the coupled stability for any prescribed range of loads, denoted by circles in the scattering domain. To demonstrate the effectiveness of the proposed methodologies, numerical and experimental results for a position–force control architecture under constant time delays are provided.},

keywords = {Absolute stability, Cascaded networks, Möbius transformation, Passivity, Teleoperation, Time delay},

pubstate = {published},

tppubtype = {article}

}

@article{9899364,

title = {Digital Twin-Driven Vehicular Task Offloading and IRS Configuration in the Internet of Vehicles},

author = {Xiaoming Yuan and Jiahui Chen and Ning Zhang and Jianbing Ni and Fei Richard Yu and Victor C. M. Leung},

url = {https://ieeexplore.ieee.org/abstract/document/9899364},

doi = {10.1109/TITS.2022.3204585},

issn = {1558-0016},

year  = {2022},

date = {2022-09-21},

urldate = {2022-09-21},

journal = {IEEE Transactions on Intelligent Transportation Systems},

pages = {1-15},

abstract = {Digital Twin (DT) and Intelligent Reflective Surface (IRS), the most two promising technologies of 6G make the Internet of Vehicles (IoV) more adaptive. However, future autonomous driving needs powerful networking resources and high-quality wireless communications to guarantee the Quality of Service (QoS). Especially considering the time-varying physical operating environments of IoV, it is extremely urgent to improve resource utilization and wireless channel quality. In this work, we propose a Digital Twin-Driven Vehicular Task Offloading and IRS Configuration Framework (DTVIF) to efficiently monitor, learn, and manage the IoV. Specifically, we adopt Mobile Edge Computing (MEC) and IRS to provide augmented computing capacities for vehicles and improve transmission performance when vehicles communicate to MEC servers. DT is employed to achieve real-time data collection and digital representation of physical operating environments of IoV to better support decisions making. In order to reduce the overall delay and energy consumption of DTVIF, we propose a Two-Stage Optimization for Jointly Optimizing Task Offloading and IRS Configuration (TSJTI) algorithm based on Deep Reinforcement Learning (DRL) and Transfer Learning (TFL). In the first stage, we introduce Double Deep $Q$ -learning Networks (DDQN) to find the optimal offloading decision. In the second stage, based on the parameters learned from the first stage, we migrate the parameters from the first stage to find the optimal IRS configuration based on the Deep Deterministic Policy Gradient (DDPG) method. The simulations demonstrate that the proposed algorithm can effectively reduce the processing latency of task offloading and reduce the average energy consumption in DTVIF.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9895280,

title = {Differentially Private Set Intersection for Asymmetrical ID Alignment},

author = {Yuanyuan He and Xinyu Tan and Jianbing Ni and Laurence T. Yang and Xianjun Deng},

url = {https://ieeexplore.ieee.org/abstract/document/9895280},

doi = {10.1109/TIFS.2022.3207911},

issn = {1556-6021},

year  = {2022},

date = {2022-09-19},

urldate = {2022-01-01},

journal = {IEEE Transactions on Information Forensics and Security},

pages = {1-1},

abstract = {Private Set Intersection (PSI) is typically used to achieve ID alignment with protection of IDs in the preparation phase of Vertical Federated Learning (VFL). However, existing PSI approaches are limited to protecting IDs that are outside the intersection of participants, and most ignore the sensitivity of intersection for a weak party in an asymmetrical ID alignment. Since the set size of the strong party is much greater than the weak party’s in an asymmetrical federation, and the intersection usually accounts for a substantial part of the weak party set, the weak party’s sensitive sample IDs would be severely compromised through sharing the intersection. To address this issue, we propose Differentially private PSI Cardinality and PSI (DPSI-CA, DPSI) protocols, which protect the intersection cardinality and sensitive IDs inside the intersect ion for the weak party, respectively. First, DPSI-CA encodes IDs in binary notation, and combines them with the GM encryption, to perform the ID-matchmaking by executing bitwise plaintext XOR. Then, the encrypted matching results are independently perturbed using randomized responses to produce differentially private outputs for PSI-CA, and its unbiased estimate is added to remove the deviation brought by the randomization. Furthermore, DPSI fuses Pseudo-Random Function (PRF)-based zero sharing, garbled Bloom filter, and Oblivious PRF (OPRF)-based shares reconstruction, to successfully reconstruct the shares corresponding to sampled IDs in the intersection. Meanwhile, a randomized response is used to sample the inputs and perturb the outputs of the OPRF-based shares reconstruction, producing a randomly sampled intersection for the weak party and differentially private intersection for the strong party. Finally, the privacy analysis shows that our protocols provide differential privacy for the weak party’s sensitive sample IDs, and extensive experiment results illustrate the feasibility of the asymmetrical ID alignment involving millions of IDs.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{HAJIAN2022104012,

title = {Bagged tree ensemble modelling with feature selection for isometric EMG-based force estimation},

author = {Gelareh Hajian and Behnam Behinaein and Ali Etemad and Evelyn Morin},

url = {https://www.sciencedirect.com/science/article/pii/S1746809422004876},

doi = {https://doi.org/10.1016/j.bspc.2022.104012},

issn = {1746-8094},

year  = {2022},

date = {2022-09-01},

urldate = {2022-01-01},

journal = {Biomedical Signal Processing and Control},

volume = {78},

pages = {104012},

abstract = {EMG-based force estimation is crucial in applications, such as control of powered prosthetic and rehabilitation devices. Most previous studies focus on intra-subject force modelling. However, a generalized EMG-force estimation model, which is capable of estimating force across users, is needed for surgical and rehabilitation robotics. In this study, EMG signals are recorded from the long head and short head of the biceps brachii, and brachioradialis using 3 linear surface electrode arrays, during isometric elbow flexions, at different joint angles and forearm postures, while recording the induced force at the wrist. The recorded EMGs are pre-processed and segmented, and 336 time and frequency domain features are extracted from 21 EMG channels. We explore developing a model that can perform well across subjects, where Bagged Tree Ensemble (BTE) models are used to learn the non-linear, complex relationships between the EMG and force data. The BTE models are compared with several machine learning approaches. The BTE model performs best, giving an average normalized mean squared error (%NMSE) of 5.65±16.24%. To reduce the dimensionality of the feature space and improve force estimation performance, a novel feature selection technique, called modified sequential feature selection (MSFS) is implemented and compared to other commonly used feature selection methods. Results show that the MSFS algorithm outperformed other methods tested, significantly reducing the force estimation error. We also found that there was no effect of forearm posture and joint angle on force modelling accuracy, permitting the development of an isometric force estimation model generalized across participants and arm positions.},

keywords = {Bagged Tree Ensemble (BTE), Force estimation, High-density (HD) recording, Isometric contraction, Surface electromyogram (EMG)},

pubstate = {published},

tppubtype = {article}

}

@article{10.1145/3564696,

title = {Multiple Mobile Robot Task and Motion Planning: A Survey},

author = {Luka Antonyshyn and Jefferson Silveira and Sidney Givigi and Joshua Marshall},

url = {https://doi.org/10.1145/3564696},

doi = {10.1145/3564696},

issn = {0360-0300},

year  = {2022},

date = {2022-09-01},

urldate = {2022-09-01},

journal = {ACM Comput. Surv.},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

abstract = {With recent advances in mobile robotics, autonomous systems, and artificial intelligence, there is a growing expectation that robots are able to solve complex problems. Many of these problems require multiple robots working cooperatively in a multi-robot system. Complex tasks may also include the interconnection of task-level specifications with robot motion-level constraints. Many recent works in the literature use multiple mobile robots to solve these complex tasks by integrating task and motion planning. We survey recent contributions to the field of combined task and motion planning for multiple mobile robots by categorizing works based on their underlying problem representations, and identify possible directions for future research. We propose a taxonomy for task and motion planning based on system capabilities, applicable to multi-robot and single-robot systems.},

note = {Just Accepted},

keywords = {autonomous robotics, Autonomous Vehicles, cooperation, mobile robotics, motion planning, Task and motion planning, task planning},

pubstate = {published},

tppubtype = {article}

}

@article{10.1145/3564696b,

title = {Multiple Mobile Robot Task and Motion Planning: A Survey},

author = {Luka Antonyshyn and Jefferson Silveira and Sidney Givigi and Joshua Marshall},

url = {https://doi.org/10.1145/3564696},

doi = {10.1145/3564696},

issn = {0360-0300},

year  = {2022},

date = {2022-09-01},

urldate = {2022-09-01},

journal = {ACM Comput. Surv.},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

abstract = {With recent advances in mobile robotics, autonomous systems, and artificial intelligence, there is a growing expectation that robots are able to solve complex problems. Many of these problems require multiple robots working cooperatively in a multi-robot system. Complex tasks may also include the interconnection of task-level specifications with robot motion-level constraints. Many recent works in the literature use multiple mobile robots to solve these complex tasks by integrating task and motion planning. We survey recent contributions to the field of combined task and motion planning for multiple mobile robots by categorizing works based on their underlying problem representations, and identify possible directions for future research. We propose a taxonomy for task and motion planning based on system capabilities, applicable to multi-robot and single-robot systems.},

note = {Just Accepted},

keywords = {autonomous robotics, Autonomous Vehicles, cooperation, mobile robotics, motion planning, Task and motion planning, task planning},

pubstate = {published},

tppubtype = {article}

}

@article{9854055,

title = {Blockchain-Based Credential Management for Anonymous Authentication in SAGVN},

author = {Dongxiao Liu and Huaqing Wu and Cheng Huang and Jianbing Ni and Xuemin Shen},

url = {https://ieeexplore.ieee.org/abstract/document/9854055

},

doi = {10.1109/JSAC.2022.3196091},

issn = {1558-0008},

year  = {2022},

date = {2022-08-10},

urldate = {2022-08-10},

journal = {IEEE Journal on Selected Areas in Communications},

volume = {40},

number = {10},

pages = {3104-3116},

abstract = {In this paper, we propose a blockchain-based collaborative credential management scheme for anonymous authentication in space-air-ground integrated vehicular networks (SAGVN), named SAG-BC. First, we build a consortium blockchain among service providers and design a distributed system setup (DSS) scheme to securely generate public parameters for issuing credentials. Second, we design a collaborative credential issuance (CCI) scheme to generate a succinct and easy-to-manage subscription credential. The credential can be used by users to access different access points in SAGVN efficiently without revealing true identities from the authentication messages. With co-designs of zero-knowledge proofs and succinct on-chain commitments, SAG-BC provides efficient verifiability and incentives for credential management operations in SAGVN. By doing so, expensive on-chain storage and computational overheads are reduced in the DSS and CCI. Finally, we conduct a thorough security analysis to demonstrate that SAG-BC achieves security and verifiability for credential management in SAGVN. We set up a real-world blockchain network and conduct extensive experiments to show the feasibility and efficiency of SAG-BC.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{MOULTON2022,

title = {Online control of discrete-event systems: A survey},

author = {Richard Hugh Moulton and Karen Rudie},

url = {https://www.sciencedirect.com/science/article/pii/S1367578822000931},

doi = {https://doi.org/10.1016/j.arcontrol.2022.08.002},

issn = {1367-5788},

year  = {2022},

date = {2022-08-06},

urldate = {2022-01-01},

journal = {Annual Reviews in Control},

abstract = {In control theory, as in other areas of engineering research, there is an inherent tension between the breadth of a technique’s applicability and its mathematical tractability. For the area of discrete-event systems (DES), this manifested itself in a theory of supervisory control that originally provided correct-by-construction guarantees for offline solutions to a restricted kind of deterministic process. Follow-on work extended the reach of these techniques to a number of new settings, notably the development of online control without sacrificing any of the original DES performance guarantees. The ability to enact online control opened the door to applying DES techniques to the adaptive control processes presented by modern technologies: processes with dynamic and time-varying natures, whose characteristics may be understood poorly or not at all. Although many works have built on the seminal work of online control in DES, we believe that these ideas have not reached their full potential due to the difficulty in translating them to adjacent fields. In this survey, we look back at 30 years of research concerning the online control of DES and closely related limited lookahead policies with an eye to making the works accessible to practitioners in the broader control theory and artificial intelligence communities. We conclude with some thoughts on future research directions for the further development and application of online DES control techniques to problems requiring intelligent control in our modern world.},

keywords = {Artificial Intelligence, Discrete-event systems, Limited lookahead, Online control, Supervisory control},

pubstate = {published},

tppubtype = {article}

}

@article{9857917,

title = {Bimodal Dynamic Swarms},

author = {Peter Travis Jardine and Sidney N. Givigi},

doi = {10.1109/ACCESS.2022.3198993},

issn = {2169-3536},

year  = {2022},

date = {2022-07-27},

urldate = {2022-01-01},

journal = {IEEE Access},

volume = {10},

pages = {94487-94495},

abstract = {This paper presents a bimodal control strategy for transitioning between different topologies of flocking and dynamic structures. The work is motivated by applications where agents must pursue and close in on a target prior to carrying out more sophisticated tasks. Specifically, it builds on previous work in consensus-based flocking to define a new type of dynamic target pursuit and capturing method called dynamic enspherement. The problem is formulated in terms of the canonical Reynolds rules and overlapping planes of encirclement using quaternions of arbitrary orientation. A new method for transitioning between flocking and enspherement is presented, the smoothness of which is demonstrated mathematically. The proposed approach is validated in a series of simulations on swarms of particles with double-integrator dynamics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FARLEY2022102629,

title = {How to pick a mobile robot simulator: A quantitative comparison of CoppeliaSim, Gazebo, MORSE and Webots with a focus on accuracy of motion},

author = {Andrew Farley and Jie Wang and Joshua A. Marshall},

url = {https://www.sciencedirect.com/science/article/pii/S1569190X22001046},

doi = {https://doi.org/10.1016/j.simpat.2022.102629},

issn = {1569-190X},

year  = {2022},

date = {2022-07-18},

urldate = {2022-01-01},

journal = {Simulation Modelling Practice and Theory},

volume = {120},

pages = {102629},

abstract = {The number of available tools for dynamic simulation of robots has been growing rapidly in recent years. However, to the best of our knowledge, there are very few reported quantitative comparisons of the most widely-used robot simulation tools. This article attempts to partly fill this gap by providing quantitative and objective comparisons of four widely-used simulation packages for mobile robots. The comparisons reported here were conducted by obtaining data from a real Husky A200 mobile robot driving on mixed terrains as ground truth and by simulating a 3D mobile robot model in a developed identical simulation world of these terrains for each simulator. We then compared the simulation outputs with real, measured results by weighted metrics. Based on our experiments and selected metrics, we conclude that CoppeliaSim is currently the best performing simulator, although Gazebo is not far behind and is a good alternative.},

keywords = {Quantitative analysis, Robot Operating System (ROS), Robot simulation, Robot software},

pubstate = {published},

tppubtype = {article}

}

@article{9825705,

title = {Multimodal Estimation of Endpoint Force During Quasi-Dynamic and Dynamic Muscle Contractions Using Deep Learning},

author = {Gelareh Hajian and Evelyn Morin and Ali Etemad},

url = {https://ieeexplore.ieee.org/document/9825705},

doi = {10.1109/TIM.2022.3189632},

issn = {1557-9662},

year  = {2022},

date = {2022-07-11},

urldate = {2022-01-01},

journal = {IEEE Transactions on Instrumentation and Measurement},

volume = {71},

pages = {1-11},

abstract = {Accurate force/torque estimation is essential for applications such as powered exoskeletons, robotics, and rehabilitation. However, force/torque estimation under dynamic conditions is challenging due to changing joint angles, force levels, muscle lengths, and movement speeds. We propose a novel method to accurately model the generated force under isotonic, isokinetic (quasi-dynamic), and fully dynamic conditions. Our solution uses a deep multimodal convolutional neural network (CNN) to learn from multimodal electromyogram-inertial measurement unit (EMG-IMU) data and estimate the generated force for elbow flexion and extension, for both intra- and intersubject schemes. The proposed deep multimodal CNN extracts representations from EMG (in time and frequency domains) and IMU (in time domain) and aggregates them to obtain an effective embedding for force estimation. We describe a new dataset containing EMG, IMU, and output force data, collected under a number of different experimental conditions, and use this dataset to evaluate our proposed method. The results show the robustness of our approach in comparison to other baseline methods and those in the literature, in different experimental setups and validation schemes. The obtained $R^2$ values are 0.91 ± 0.034, 0.87 ± 0.041, and 0.81 ± 0.037 for the intrasubject and 0.81 ± 0.048, 0.64 ± 0.037, and 0.59 ± 0.042 for the intersubject scheme, during isotonic, isokinetic, and dynamic contractions, respectively. In addition, our results indicate that force estimation improves significantly when the kinematic information (IMU data) is included. Average improvements of 13.95%, 118.18%, and 50.0% (intrasubject) and 28.98%, 41.18%, and 137.93% (intersubject) for isotonic, isokinetic, and dynamic contractions, respectively, are achieved.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9878045,

title = {Astraea: Anonymous and Secure Auditing Based on Private Smart Contracts for Donation Systems},

author = {Meng Li and Yifei Chen and Liehaung Zhu and Zijian Zhang and Jianbing Ni and Chhagan Lal and Mauro Conti},

url = {https://ieeexplore.ieee.org/abstract/document/9878045},

doi = {10.1109/TDSC.2022.3204287},

issn = {1941-0018},

year  = {2022},

date = {2022-07-05},

urldate = {2022-01-01},

journal = {IEEE Transactions on Dependable and Secure Computing},

pages = {1-17},

abstract = {Many regions are in urgent need of facial masks for slowing down the spread of COVID-19. To fight the pandemic, people are contributing masks through donation systems. Most existing systems are built on a centralized architecture which is prone to the single point of failure and lack of transparency. Blockchain-based solutions neglect fundamental privacy concerns (donation privacy) and security attacks (collusion attack, stealing attack). Moreover, current auditing solutions are not designed to achieve donation privacy, thus not appropriate in our context. In this work, we design a decentralized, anonymous, and secure auditing framework Astraea based on private smart contracts for donation systems. Specifically, we integrate a Distribute Smart Contract (DiSC) with an SGX Enclave to distribute donations, prove the integrity of donation number (intention) and donation sum while preserving donation privacy. With DiSC, we design a Donation Smart Contract to refund deposits and defend against the stealing attack the collusion attack from malicious collector and transponder. We formally define and prove the privacy and security of Astraea by using security reduction. We build a prototype of Astraea to conduct extensive performance analysis. Experimental results demonstrate that Astraea is practically efficient in terms of both computation and communication.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{GILLHAM2022114389,

title = {Measuring support reactions and damage detection in steel beams using distributed strain sensing},

author = {Jack GILLHAM and Evan C. BENTZ and Neil A. HOULT},

url = {https://www.sciencedirect.com/science/article/pii/S0141029622005041},

doi = {https://doi.org/10.1016/j.engstruct.2022.114389},

issn = {0141-0296},

year  = {2022},

date = {2022-07-01},

urldate = {2022-01-01},

journal = {Engineering Structures},

volume = {262},

pages = {114389},

abstract = {While visual inspections are an important tool in the assessment of steel bridges, they cannot provide quantitative information about the bridge’s behavior. Distributed fiber optic sensors (DFOS) have the potential to provide added insight into the performance of bridges through the measurement of full strain profiles along a member as well as other key performance indicators that can be derived from these measurements. This study investigates the use of DFOS measurements to derive support reactions and detect local damage along the flexural members in a bridge. A series of load tests were undertaken to develop the method for support reaction estimation, starting with a simply supported beam, then continuous beams, and then finally a full model bridge. The beam test support reactions were evaluated against load cell measurements and variations in geometry were shown to have an impact on the measurements that could be accounted for through calibration. The model bridge reactions matched the total applied load and showed the expected distribution for the loading configuration applied. A second model bridge test was undertaken where the shear stress in the connection between the beams and the slab exceeded the capacity of the connection and localized damage occurred. Using the DFOS measurements, the neutral axis was calculated and used to detect this localized damage.},

keywords = {Beams, Damage detection, Distributed fiber optic sensing, Support reactions},

pubstate = {published},

tppubtype = {article}

}

@article{Ean2022b,

title = {Epistemic interpretations of decentralized discrete-event system problems},

author = {Richard Ean, Karen Rudie},

url = {https://doi.org/10.1007/s10626-022-00363-7},

doi = {10.1007/s10626-022-00363-7},

year  = {2022},

date = {2022-06-22},

urldate = {2022-06-22},

journal = {Discrete Event Dynamic Systems},

abstract = {This paper presents epistemic characterizations to co-observability conditions in decentralized supervisory control of discrete-event systems. The logical characterizations provide more intuitive interpretations of the various co-observability conditions, and make immediately apparent the relations between the conditions. Closures under set union of some of the conditions are also discussed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{callananmacq,

title = {MACQ: A Holistic View of Model Acquisition Techniques},

author = {Ethan Callanan and Rebecca De Venezia and Victoria Armstrong and Alison Paredes and Tathagata Chakraborti and Christian Muise},

year  = {2022},

date = {2022-06-01},

urldate = {2022-06-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9785901,

title = {Controller Based Interactive Proof to Ensure Trust in Multi-Agent Systems},

author = {Jean-Alexis Delamer and Sidney Givigi},

url = {https://ieeexplore.ieee.org/abstract/document/9785901},

doi = {10.1109/TAC.2022.3179217},

issn = {1558-2523},

year  = {2022},

date = {2022-05-31},

urldate = {2022-01-01},

journal = {IEEE Transactions on Automatic Control},

pages = {1-1},

abstract = {When multiple agents need to perform tasks that need cooperation, communication is necessary for coordination and also to assess completion. In these cases, trust needs to be guaranteed so agents know if others are following a common strategy or if they are not cooperating. If communication is explicit, other agents, including agents not involved directly in the mission, can forge information and lead agents to believe that they are behaving according to the mission plan. Several methods have been proposed in the literature and in this paper, we propose a novel method based on interactive proofs in which trust between two agents is asserted by one agent demonstrating to the other that both follow the same mission plan. We formally represent the problem as a series of Markov Decision Processes and demonstrate that the formulation is complete and sound. Simulations of multiple agents in a maze problem demonstrate the behaviour of the system.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}