@article{Zhang2024MultiModal,

title = {Multimodal Intention Recognition Combining Head Motion and Throat Vibration for Underwater Superlimbs},

author = {Rongzheng Zhang and Wanghongjie Qiu and Jianuo Qiu and Yuqin Guo and Chengxiao Dong and Tuo Zhang and Juan Yi and Chaoyang Song and Harry Asada and Fang Wan},

doi = {10.1109/TASE.2025.3554036},

year  = {2025},

date = {2025-03-20},

urldate = {2025-03-20},

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

volume = {0},

number = {0},

pages = {0},

abstract = {This paper presents a novel solution for underwater intention recognition that simultaneously detects head motion and throat vibration, enhancing multimodal human-robot interactions for underwater diving. The system pairs with an underwater supernumerary robotic limb (SuperLimb), providing propulsion assistance to reduce the diver's physical load and mental fatigue. An inertial measurement unit monitors head motion, while a throat microphone captures vocal vibrations. Learning algorithms process these signals to accurately interpret the diver's intentions and map them to the SuperLimb for posture management. The system features a compact design optimized for diving scenarios and includes a multimodal, real-time classification algorithm to distinguish various head motions and vocal signals. By collecting and analyzing underwater throat vibration data, the study demonstrates the feasibility of this approach, enabling continuous motion commands for enhanced diving assistance. The results show that the head motion recognition component of the system achieved a high classification accuracy of 95%, and throat vibration classification reached 86% accuracy on land and 89% underwater for various purposes.},

keywords = {Authorship - Co-Author, JCR Q1, Jour - IEEE Trans. Autom. Sci. Eng. (T-ASE)},

pubstate = {published},

tppubtype = {article}

}

@article{Pan2023ANovel,

title = {A Novel Post-Processing Strategy to Improve the Accuracy of Complete-Arch Intraoral Scanning for Implants: An In Vitro Study},

author = {Yu Pan and Xuanyi Dai and Fang Wan and Chaoyang Song and James KH Tsoi and Edmond HN Pow},

doi = {10.1016/j.jdent.2023.104761},

year  = {2023},

date = {2023-12-01},

urldate = {2023-12-01},

journal = {Journal of Dentistry},

volume = {139},

issue = {December},

pages = {104761},

abstract = {[Objectives] To develop a new post-processing strategy that utilizes an auxiliary device to adjust intraoral scans and improve the accuracy of 3D models of complete-arch dental implants.



[Materials and methods] An edentulous resin model with 6 dental implants was prepared. An auxiliary device, consisting of an opaque base and artificial landmarks, was fabricated and mounted onto the resin model. Twenty intraoral scans (raw scans) were taken using this setup. A new post-processing strategy was proposed to adjust the raw scans using reverse engineering software (verified group). Additionally, ten conventional gypsum casts were duplicated and digitized using a laboratory scanner. The linear and angular trueness and precision of the models were evaluated and compared. The effect of the proposed strategy on the accuracy of complete-arch intraoral scans was analyzed using one-way ANOVA.



[Results] The linear trueness (29.7 µm) and precision (24.8 µm) of the verified group were significantly better than the raw scans (46.6 µm, 44.7 µm) and conventional casts (51.3 µm, 36.5 µm), particularly in cross-arch sites. However, the angular trueness (0.114°) and precision (0.085°) of the conventional casts were significantly better than both the verified models (0.298°, 0.168°) and the raw scans (0.288°, 0.202°).



[Conclusions] The novel post-processing strategy is effective in enhancing the linear accuracy of complete-arch implant IO scans, especially in cross-arch sites. However, further improvement is needed to eliminate the angular deviations.



[Clinical significance] Errors generated from intraoral scanning in complete edentulous arches exceed the clinical threshold. The elimination of stitching errors in the raw scans particularly in the cross-arch sites, through the proposed post-processing strategy would enhance the accuracy of complete-arch implant prostheses.},

keywords = {Authorship - Co-Author, JCR Q1, Jour - J. Dent. (JoD)},

pubstate = {published},

tppubtype = {article}

}

@article{Yang2023TacGNN,

title = {TacGNN: Learning Tactile-based In-hand Manipulation with a Blind Robot using Hierarchical Graph Neural Network},

author = {Linhan Yang and Bidan Huang and Qingbiao Li and Ya-Yen Tsai and Wang Wei Lee and Chaoyang Song and Jia Pan},

doi = {10.1109/LRA.2023.3264759},

year  = {2023},

date = {2023-04-05},

urldate = {2023-04-05},

journal = {IEEE Robotics and Automation Letters},

volume = {8},

number = {6},

issue = {June},

pages = {3605-3612},

abstract = {In this letter, we propose a novel framework for tactile-based dexterous manipulation learning with a blind anthropomorphic robotic hand, i.e. without visual sensing. First, object-related states were extracted from the raw tactile signals by a graph-based perception model - TacGNN. The resulting tactile features were then utilized in the policy learning of an in-hand manipulation task in the second stage. This method was examined by a Baoding ball task - simultaneously manipulating two spheres around each other by 180 degrees in hand. We conducted experiments on object states prediction and in-hand manipulation using a reinforcement learning algorithm (PPO). Results show that TacGNN is effective in predicting object-related states during manipulation by decreasing the RMSE of prediction to 0.096 cm comparing to other methods, such as MLP, CNN, and GCN. Finally, the robot hand could finish an in-hand manipulation task solely relying on the robotic own perception - tactile sensing and proprioception. In addition, our methods are tested on three tasks with different difficulty levels and transferred to the real robot without further training.},

keywords = {Authorship - Co-Author, JCR Q2, Jour - IEEE Robot. Autom. Lett. (RA-L), Special - Dual-Track},

pubstate = {published},

tppubtype = {article}

}

@article{Tian2023SamplingBased,

title = {Sampling-Based Planning for Retrieving Near-Cylindrical Objects in Cluttered Scenes Using Hierarchical Graphs},

author = {Hao Tian and Chaoyang Song and Changbo Wang and Xinyu Zhang and Jia Pan},

doi = {10.1109/TRO.2022.3191596},

year  = {2023},

date = {2023-02-01},

urldate = {2023-02-01},

journal = {IEEE Transactions on Robotics},

volume = {39},

number = {1},

issue = {February},

pages = {165-182},

abstract = {We present an incremental sampling-based task and motion planner for retrieving near-cylindrical objects, like bottle, in cluttered scenes, which computes a plan for removing obstacles to generate a collision-free motion of a robot to retrieve the target object. Our proposed planner uses a two-level hierarchy, including the first-level roadmap for the target object motion and the second-level retrieval graph for the entire robot motion, to aid in deciding the order and trajectory of object removal. We use an incremental expansion strategy to update the roadmap and retrieval graph from the collisions between the target object, the robot, and the obstacles, in order to optimize the object removal sequence. The performance of our method is highlighted in several benchmark scenes, including a fixed robotic arm in a cluttered scene with known obstacle locations and a scene, where locations of some objects or even the target object are unknown due to occlusions. Our method can also efficiently solve the high-dimensional planning problem of object retrieval using a mobile manipulator and be combined with the symbolic planner to plan complex multistep tasks. We deploy our method to a physical robot and integrate it with nonprehensile actions to improve operational efficiency. Compared to the state-of-the-art approaches, our method reduces task and motion planning time up to 24.6% with a higher success rate, and still provides a near-optimal plan.},

keywords = {Authorship - Co-Author, JCR Q1, Jour - IEEE Trans. Robot. (T-RO)},

pubstate = {published},

tppubtype = {article}

}

@article{Li2023CalibratedAnalytical,

title = {Calibrated Analytical Model for Magnetic Localization of Wireless Capsule Endoscope based on Onboard Sensing},

author = {You Li and Zhuokang Huang and Xiaobo Liu and Yu Jie and Chaoyang Song and Chengzhi Hu},

doi = {10.1017/S0263574722001849},

year  = {2023},

date = {2023-01-12},

urldate = {2023-01-12},

journal = {Robotica},

volume = {41},

number = {5},

pages = {1500-1514},

abstract = {We present an incremental sampling-based task and motion planner for retrieving near-cylindrical objects, like bottle, in cluttered scenes, which computes a plan for removing obstacles to generate a collision-free motion of a robot to retrieve the target object. Our proposed planner uses a two-level hierarchy, including the first-level roadmap for the target object motion and the second-level retrieval graph for the entire robot motion, to aid in deciding the order and trajectory of object removal. We use an incremental expansion strategy to update the roadmap and retrieval graph from the collisions between the target object, the robot, and the obstacles, in order to optimize the object removal sequence. The performance of our method is highlighted in several benchmark scenes, including a fixed robotic arm in a cluttered scene with known obstacle locations and a scene, where locations of some objects or even the target object are unknown due to occlusions. Our method can also efficiently solve the high-dimensional planning problem of object retrieval using a mobile manipulator and be combined with the symbolic planner to plan complex multistep tasks. We deploy our method to a physical robot and integrate it with nonprehensile actions to improve operational efficiency. Compared to the state-of-the-art approaches, our method reduces task and motion planning time up to 24.6% with a higher success rate, and still provides a near-optimal plan.},

keywords = {Authorship - Co-Author, JCR Q3, Jour - Robotica (ROBO)},

pubstate = {published},

tppubtype = {article}

}

@article{Yan2022TactileSuper,

title = {Tactile Super-Resolution Model for Soft Magnetic Skin},

author = {Youcan Yan and Yajing Shen and Chaoyang Song and Jia Pan},

doi = {10.1109/LRA.2022.3141449},

year  = {2022},

date = {2022-01-10},

urldate = {2022-01-10},

journal = {IEEE Robotics and Automation Letters},

volume = {7},

number = {2},

issue = {April},

pages = {2589-2596},

abstract = {Tactile sensors of high spatial resolution can provide rich contact information in terms of accurate contact location and force magnitude for robots. However, achieving a high spatial resolution normally requires a high density of tactile sensing cells (or taxels), which will inevitably lead to crowded wire connections, more data acquisition time and probably crosstalk between taxels. An alternative approach to improve the spatial resolution without introducing a high density of taxels is employing super-resolution technology. Here, we propose a novel tactile super-resolution method based on a sinusoidally magnetized soft magnetic skin, by which we have achieved a 15-fold improvement of localization accuracy (from 6 mm to 0.4 mm) as well as the ability to measure the force magnitude. Different from the existing super-resolution methods that rely on overlapping signals of neighbouring taxels, our model only relies on the local information from a single 3-axis taxel and thereby can detect multipoint contact applied on neighboring taxels and work properly even when some of the neighbouring taxels near the contact position are damaged (or unavailable). With this property, our method would be robust to damage and could potentially benefit robotic applications that require multipoint contact detection.},

keywords = {Authorship - Co-Author, JCR Q2, Jour - IEEE Robot. Autom. Lett. (RA-L), Special - Dual-Track},

pubstate = {published},

tppubtype = {article}

}

@article{Liu2021OtariidaeInspired,

title = {Otariidae-Inspired Soft-Robotic Supernumerary Flippers by Fabric Kirigami and Origami},

author = {Sicong Liu and Yuming Zhu and Zicong Zhang and Zhonggui Fang and Jiyong Tan and Jing Peng and Chaoyang Song and Harry Asada and Zheng Wang},

doi = {10.1109/TMECH.2020.3045476},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

journal = {IEEE/ASME Transactions on Mechatronics},

volume = {26},

number = {5},

issue = {October},

pages = {2747-2757},

abstract = {Wearable robotic devices are receiving rapidly growing attentions for human-centered scenarios from medical, rehabilitation, to industrial applications. Supernumerary robotic limbs have been widely investigated for the augmentation of human limb functions, both as fingers and manipulator arms. Soft robotics offers an alternative approach to conventional motor-driven robot limbs toward safer and lighter systems, while pioneering soft supernumerary limbs are strongly limited in payload and dexterity by the soft robotic design approach, as well as the fabrication techniques. In this article, we proposed a wearable supernumerary soft robot for the human forearm, inspired by the fore flippers of otariids (eared seals). A flat flipper design was adopted, differing from the finger- or arm-shaped state-of-the-art works, with multiple soft actuators embedded as different joints for manipulation dexterity. The soft actuators were designed following origami (paper folding) patterns, reinforced by kirigami (paper cutting) fabrics. With this new approach, the proposed soft flipper incorporated eight independent muscles, achieving over 20 times payload to self-weight ratio, while weighing less than 500 g. The versatility, dexterity, and payload capability were experimentally demonstrated using a fabricated prototype with proprietary actuation and control. This article demonstrates the feasibility and unique advantages of origami + kirigami soft robots as a new approach to strong, dexterous, and yet safe and lightweight wearable robotic devices.},

keywords = {Authorship - Co-Author, JCR Q1, Jour - IEEE ASME Trans. Mechatron. (TMech)},

pubstate = {published},

tppubtype = {article}

}

@article{Yan2021SoftMagnetic,

title = {Soft Magnetic Skin for Super-Resolution Tactile Sensing with Force Self-Decoupling},

author = {Youcan Yan and Zhe Hu and Zhengbao Yang and Wenzhen Yuan and Chaoyang Song and Jia Pan and Yajing Shen},

doi = {10.1126/scirobotics.abc8801},

year  = {2021},

date = {2021-02-24},

urldate = {2021-02-24},

journal = {Science Robotics},

volume = {6},

number = {51},

pages = {eabc8801},

abstract = {Human skin can sense subtle changes of both normal and shear forces (i.e., self-decoupled) and perceive stimuli with finer resolution than the average spacing between mechanoreceptors (i.e., super-resolved). By contrast, existing tactile sensors for robotic applications are inferior, lacking accurate force decoupling and proper spatial resolution at the same time. Here, we present a soft tactile sensor with self-decoupling and super-resolution abilities by designing a sinusoidally magnetized flexible film (with the thickness ~0.5 millimeters), whose deformation can be detected by a Hall sensor according to the change of magnetic flux densities under external forces. The sensor can accurately measure the normal force and the shear force (demonstrated in one dimension) with a single unit and achieve a 60-fold super-resolved accuracy enhanced by deep learning. By mounting our sensor at the fingertip of a robotic gripper, we show that robots can accomplish challenging tasks such as stably grasping fragile objects under external disturbance and threading a needle via teleoperation. This research provides new insight into tactile sensor design and could be beneficial to various applications in robotics field, such as adaptive grasping, dexterous manipulation, and human-robot interaction.},

keywords = {Authorship - Co-Author, JCR Q1, Jour - Sci. Robot. (SciRob)},

pubstate = {published},

tppubtype = {article}

}

@article{Yi2019Customizable3D,

title = {Customizable Three-Dimensional-Printed Origami Soft Robotic Joint with Effective Behavior Shaping for Safe Interactions},

author = {Juan Yi and Xiaojiao Chen and Chaoyang Song and Jianshu Zhou and Yujia Liu and Sicong Liu and Zheng Wang},

doi = {10.1109/tro.2018.2871440},

year  = {2019},

date = {2019-02-01},

urldate = {2019-02-01},

journal = {IEEE Transactions on Robotics},

volume = {35},

number = {1},

issue = {February},

pages = {114-123},

abstract = {Fast-growing interests in safe and effective robot–environment interactions stimulated global investigations on soft robotics. The inherent compliance of soft robots ensures promising safety features but drastically reduces force capability, thereby complicating system modeling and control. To tackle these limitations, a soft robotic joint with enhanced strength, servo performance, and impact behavior shaping is proposed in this paper, based on novel three-dimensional-printed soft origami rotary actuators. The complete workflow is presented from the concept of origami design and analytical modeling, joint design, fabrication, control, and validation experiments. The proposed approach facilitates a fully customizable joint design towards the desired force capability and motion range. Validation results from models and experiments using multiple fabricated prototypes proved the excellent performance linearity and superior force capability, with 18.5-N·m maximum torque under 180 kPa, and 300-g self-weight. The behavior shaping capability is achieved by a low-level joint-angle servo and a high-level variable-stiffness regulation; this significantly reduces the impact torque by 53% and ensures powerful and safe interactions. The comprehensive guidelines provide insightful references for soft robotic design for wider robotic applications.},

keywords = {Authorship - Co-Author, JCR Q1, Jour - IEEE Trans. Robot. (T-RO)},

pubstate = {published},

tppubtype = {article}

}

@article{HolttaOtto2018TheCharacteristics,

title = {The Characteristics of Innovative, Mechanical Products—10 Years Later},

author = {Katja Hölttä-Otto and Kevin Otto and Chaoyang Song and Jianxi Luo and Timothy Li and Carolyn C. Seepersad and Warren Seering},

doi = {10.1115/1.4039851},

year  = {2018},

date = {2018-08-01},

urldate = {2018-08-01},

journal = {Journal of Mechanical Design},

volume = {140},

number = {8},

issue = {August},

pages = {084501},

abstract = {Ten years prior to this paper, innovative mechanical products were analyzed and found to embody multiple innovation characteristics—an average of two more than competing products in the marketplace. At the time, it was not known whether these products would be successful over time and whether the number or type of innovation characteristics would be related with success. In this work, products from the previous study were categorized into well- and under-adopted products. Also, each product was categorized according to the type of firm that launched it: a new venture or an established firm. The innovative products enjoyed a success rate of 77% on average. The success was not dependent on the number or type of innovation characteristics embodied by the product. However, products developed in new ventures embody, on average, one more innovation characteristic and enjoy a slightly higher success rate than those launched by established firms.},

keywords = {Authorship - Co-Author, JCR Q2, Jour - J. Mech. Des. (JMD)},

pubstate = {published},

tppubtype = {article}

}

@article{Yi2018FiberReinforced,

title = {Fiber-Reinforced Origamic Robotic Actuator},

author = {Juan Yi and Xiaojiao Chen and Chaoyang Song and Zheng Wang},

doi = {10.1089/soro.2016.0079},

year  = {2018},

date = {2018-02-01},

urldate = {2018-02-01},

journal = {Soft Robotics},

volume = {5},

number = {1},

pages = {81-92},

abstract = {A novel pneumatic soft linear actuator Fiber-reinforced Origamic Robotic Actuator (FORA) is proposed with significant improvements on the popular McKibben-type actuators, offering nearly doubled motion range, substantially improved force profile, and significantly lower actuation pressure. The desirable feature set is made possible by a novel soft origamic chamber that expands radially while contracts axially when pressurized. Combining this new origamic chamber with a reinforcing fiber mesh, FORA generates very high traction force (over 150N) and very large contractile motion (over 50%) at very low input pressure (100 kPa). We developed quasi-static analytical models both to characterize the motion and forces and as guidelines for actuator design. Fabrication of FORA mostly involves consumer-grade three-dimensional (3D) printing. We provide a detailed list of materials and dimensions. Fabricated FORAs were tested on a dedicated platform against commercially available pneumatic artificial muscles from Shadow and Festo to showcase its superior performances and validate the analytical models with very good agreements. Finally, a robotic joint was developed driven by two antagonistic FORAs, to showcase the benefits of the performance improvements. With its simple structure, fully characterized mechanism, easy fabrication procedure, and highly desirable performance, FORA could be easily customized to application requirements and fabricated by anyone with access to a 3D printer. This will pave the way to the wider adaptation and application of soft robotic systems.},

keywords = {Authorship - Co-Author, JCR Q1, Jour - Soft Robot. (SORO)},

pubstate = {published},

tppubtype = {article}

}