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Zou S, Picella S, de Vries J, Kortman VG, Sakes A, Overvelde JTB. A retrofit sensing strategy for soft fluidic robots. Nat Commun 2024; 15:539. [PMID: 38225274 PMCID: PMC10789869 DOI: 10.1038/s41467-023-44517-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 12/15/2023] [Indexed: 01/17/2024] Open
Abstract
Soft robots are intrinsically capable of adapting to different environments by changing their shape in response to interaction forces. However, sensory feedback is still required for higher level decisions. Most sensing technologies integrate separate sensing elements in soft actuators, which presents a considerable challenge for both the fabrication and robustness of soft robots. Here we present a versatile sensing strategy that can be retrofitted to existing soft fluidic devices without the need for design changes. We achieve this by measuring the fluidic input that is required to activate a soft actuator during interaction with the environment, and relating this input to its deformed state. We demonstrate the versatility of our strategy by tactile sensing of the size, shape, surface roughness and stiffness of objects. We furthermore retrofit sensing to a range of existing pneumatic soft actuators and grippers. Finally, we show the robustness of our fluidic sensing strategy in closed-loop control of a soft gripper for sorting, fruit picking and ripeness detection. We conclude that as long as the interaction of the actuator with the environment results in a shape change of the interval volume, soft fluidic actuators require no embedded sensors and design modifications to implement useful sensing.
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Affiliation(s)
- Shibo Zou
- Autonomous Matter Department, AMOLF, Amsterdam, 1098 XG, The Netherlands
| | - Sergio Picella
- Autonomous Matter Department, AMOLF, Amsterdam, 1098 XG, The Netherlands
- Institute for Complex Molecular Systems and Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands
| | - Jelle de Vries
- Autonomous Matter Department, AMOLF, Amsterdam, 1098 XG, The Netherlands
| | - Vera G Kortman
- Department of Marine and Transport Technology, Delft University of Technology, Delft, 2628 CD, The Netherlands
- Bio-Inspired Technology Group, Department of BioMechanical Engineering, Delft University of Technology, Delft, 2628 CD, The Netherlands
| | - Aimée Sakes
- Bio-Inspired Technology Group, Department of BioMechanical Engineering, Delft University of Technology, Delft, 2628 CD, The Netherlands
| | - Johannes T B Overvelde
- Autonomous Matter Department, AMOLF, Amsterdam, 1098 XG, The Netherlands.
- Institute for Complex Molecular Systems and Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands.
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2
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Nam YG, Kwon BS. Prefrontal Cortex Activation during Memory Training by Virtual Drum Beating: A Randomized Controlled Trial. Healthcare (Basel) 2023; 11:2559. [PMID: 37761756 PMCID: PMC10530734 DOI: 10.3390/healthcare11182559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 09/11/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023] Open
Abstract
The use of virtual reality (VR) content in neurological disorders with cognitive impairment is increasing. We have developed a device that incorporates virtual drum beating content, designed for digit memorization training. This study aimed to investigate the effects of realistic cognitive training on brain activity using functional near-infrared spectroscopy (fNIRS). Thirty healthy individuals were recruited and randomly assigned into two groups: conventional cognitive exercise (CCE) and a realistic cognitive exergame (RCE). Subjects in the CCE group underwent memory training by memorizing numbers displayed on a computer screen and then writing them on paper. The main outcome measure was the oxyhemoglobin level in the dorsolateral prefrontal cortex (DLPFC). As a result, the average number of digits was 7.86 ± 0.63 for the CCE and 7.6 ± 0.82 for the RCE. The mean difference in ΔHbO was 1.417 ± 0.616 μm (p = 0.029) in channel 2, located in the right DLPFC. Channel 7 and channel 10, which measured activations in the hypothesized medial orbitofrontal cortex (OFC), also showed a significant mean difference of ΔHbO. DLPFC and OFC presented higher activation in the RCE group (p < 0.05), attributable to the simultaneous memory training and virtual drum beating, which provided various sensory inputs (visual, auditory, and vibration). Although DLPFC involvement in cognitive processes remains controversial, our findings suggest that realistic memory training using drumming content can lead to safer activation of the DLPFC compared to conventional cognitive training.
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Affiliation(s)
- Yeon-Gyo Nam
- Department of Physical Therapy, Sun Moon University, Asan 31460, Republic of Korea;
| | - Bum-Sun Kwon
- Department of Rehabilitation Medicine, School of Medicine, Dongguk University, Goyang 10326, Republic of Korea
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3
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Wang L, Lam J, Chen X, Li J, Zhang R, Su Y, Wang Z. Soft Robot Proprioception Using Unified Soft Body Encoding and Recurrent Neural Network. Soft Robot 2023; 10:825-837. [PMID: 37001175 DOI: 10.1089/soro.2021.0056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
Abstract
Compared with rigid robots, soft robots are inherently compliant and have advantages in the tasks requiring flexibility and safety. But sensing the high dimensional body deformation of soft robots is a challenge. Encasing soft strain sensors into the internal body of soft robots is the most popular solution to address this challenge. But most of them usually suffer from problems like nonlinearity, hysteresis, and fabrication complexity. To endow the soft robots with body movement awareness, this work presents a bioinspired architecture by taking cues from human proprioception system. Differing from the popular usage of smart material-based sensors embedded in soft actuators, we created a synthetic analog to the human muscle system, using paralleled soft pneumatic chambers to serve as receptors for sensing body deformation. We proposed to build the system with redundant receptors and explored deep learning tools for generating the kinematic model. Based on the proposed methodology, we demonstrated the design of three degrees of freedom continuum joint and how its kinematic model was learned from the unified pressure information of the actuators and receptors. In addition, we investigated the response of the soft system to receptor failures and presented both hardware and software level solutions for achieving graceful degradation. This approach offers an alternative to enable soft robots with proprioception capability, which will be useful for closed-loop control and interaction with environment.
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Affiliation(s)
- Liangliang Wang
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - James Lam
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Xiaojiao Chen
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Jing Li
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Runzhi Zhang
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Yinyin Su
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Zheng Wang
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
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4
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Joe S, Bliah O, Magdassi S, Beccai L. Jointless Bioinspired Soft Robotics by Harnessing Micro and Macroporosity. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2302080. [PMID: 37323121 PMCID: PMC10427402 DOI: 10.1002/advs.202302080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Indexed: 06/17/2023]
Abstract
Although natural continuum structures, such as the boneless elephant trunk, provide inspiration for new versatile grippers, highly deformable, jointless, and multidimensional actuation has still not been achieved. The challenging pivotal requisites are to avoid sudden changes in stiffness, combined with the capability of providing reliable large deformations in different directions. This research addresses these two challenges by harnessing porosity at two levels: material and design. Based on the extraordinary extensibility and compressibility of volumetrically tessellated structures with microporous elastic polymer walls, monolithic soft actuators are fabricated by 3D printing unique polymerizable emulsions. The resulting monolithic pneumatic actuators are printed in a single process and are capable of bidirectional movements with just one actuation source. The proposed approach is demonstrated by two proof-of-concepts: a three-fingered gripper, and the first ever soft continuum actuator that encodes biaxial motion and bidirectional bending. The results open up new design paradigms for continuum soft robots with bioinspired behavior based on reliable and robust multidimensional motions.
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Affiliation(s)
- Seonggun Joe
- Soft BioRobotics PerceptionIstituto Italiano di Tecnologia (IIT)Genova16163Italy
| | - Ouriel Bliah
- Casali Center for Applied ChemistryInstitute of ChemistryCenter for Nanotechnology and Nanoscience Hebrew University of JerusalemJerusalem9190401Israel
| | - Shlomo Magdassi
- Singapore‐HUJ Alliance for Research and Enterprise (SHARE)Smart Grippers for Soft Robotics (SGSR)Campus for Research Excellence and Technological Enterprise (CREATE)Singapore138602Singapore
| | - Lucia Beccai
- Soft BioRobotics PerceptionIstituto Italiano di Tecnologia (IIT)Genova16163Italy
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5
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Abstract
Underwater robotic gliders exploit gravity and buoyancy for long-distance cruising with ultra-low energy consumptions, making them ideal for open ocean surveying operations. However, the gliding-based motion generation principle also prevents their maneuverability, limiting their use in the short distances that are usually encountered in harbors or coastal scenarios. In this work, an innovative underwater glider robot is developed, enabling maneuverability through the introduction of an efficiently actuated caudal fin with bidirectional turning capabilities. In addition, modular actuator units, based on soft actuated materials, are integrated to control pitch angle by dynamically shifting the center of mass from the center of buoyancy. As a result, the high energy efficiency feature of the gliders is maintained, while high maneuverability is also achieved. The design concept, modeling of key components, and framework for control are presented, with the prototyped glider tested in a series of bench and field trials for validation of its motion performance.
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6
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Wang L, Li Q, Lam J, Wang Z. Tactual Recognition of Soft Objects From Deformation Cues. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2021.3119393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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7
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Tan Q, Chen Y, Liu J, Zou K, Yi J, Liu S, Wang Z. Underwater Crawling Robot With Hydraulic Soft Actuators. Front Robot AI 2021; 8:688697. [PMID: 34513936 PMCID: PMC8427137 DOI: 10.3389/frobt.2021.688697] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 08/02/2021] [Indexed: 02/05/2023] Open
Abstract
Benthic operation plays a vital role in underwater applications, where crawling robots have advantages compared with turbine-based underwater vehicles, in locomotion accuracy, actuation efficiency, current resistance, and in carrying more payloads. On the other hand, soft robots are quickly trending in underwater robotic design, with their naturally sealed body structure and intrinsic compliance both desirable for the highly unstructured and corrosive underwater environment. However, the limitations resulting directly from the inherent compliance, in structural rigidity, actuation precision, and limited force exertion capability, have also restricted soft robots in underwater applications. To date soft robots are adopted mainly as grippers and manipulators for atraumatic sampling, rather than as locomotion platforms. In this work, we present a soft-robotic approach to designing underwater crawling robots, with three main innovations: 1) using rigid structural components to strategically reinforce the otherwise omni-directionally flexible soft actuators, drastically increasing their loading capability and actuation precision; 2) proposing a rigid–soft hybrid multi-joint leg design, with quasi-linear motion range and force exertion, while maintaining excellent passive impact compliance by exploiting the inherent flexibility of soft actuators; 3) developing a novel valve-free hydraulic actuation system with peristaltic pumps, achieving a compact, lightweight, and untethered underwater crawling robot prototype with a 5:1 payload-to-weight ratio and multi-gait capability. The prototype was tested for design verification and showcasing the advantages of the proposed hybrid mechanism and actuation approach.
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Affiliation(s)
- Qinlin Tan
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yishan Chen
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Jianhui Liu
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Kehan Zou
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Juan Yi
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China.,Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, China.,Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Sicong Liu
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China.,Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, China.,Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Zheng Wang
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China.,Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, China.,Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
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8
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Wang B, Guo W, Feng S, Hongdong Y, Wan F, Song C. Volumetrically Enhanced Soft Actuator With Proprioceptive Sensing*. IEEE Robot Autom Lett 2021. [DOI: 10.1109/lra.2021.3072859] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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9
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Dong X, Tang C, Jiang S, Shao Q, Zhao H. Increasing the Payload and Terrain Adaptivity of an Untethered Crawling Robot Via Soft-Rigid Coupled Linear Actuators. IEEE Robot Autom Lett 2021. [DOI: 10.1109/lra.2021.3061342] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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10
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Jékely G, Godfrey-Smith P, Keijzer F. Reafference and the origin of the self in early nervous system evolution. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190764. [PMID: 33550954 PMCID: PMC7934971 DOI: 10.1098/rstb.2019.0764] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/07/2020] [Indexed: 12/20/2022] Open
Abstract
Discussions of the function of early nervous systems usually focus on a causal flow from sensors to effectors, by which an animal coordinates its actions with exogenous changes in its environment. We propose, instead, that much early sensing was reafferent; it was responsive to the consequences of the animal's own actions. We distinguish two general categories of reafference-translocational and deformational-and use these to survey the distribution of several often-neglected forms of sensing, including gravity sensing, flow sensing and proprioception. We discuss sensing of these kinds in sponges, ctenophores, placozoans, cnidarians and bilaterians. Reafference is ubiquitous, as ongoing action, especially whole-body motility, will almost inevitably influence the senses. Corollary discharge-a pathway or circuit by which an animal tracks its own actions and their reafferent consequences-is not a necessary feature of reafferent sensing but a later-evolving mechanism. We also argue for the importance of reafferent sensing to the evolution of the body-self, a form of organization that enables an animal to sense and act as a single unit. This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.
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Affiliation(s)
- Gáspár Jékely
- Living Systems Institute, University of Exeter, Stocker Road, Exeter, EX4 4QD, UK
| | - Peter Godfrey-Smith
- School of History and Philosophy of Science, University of Sydney, New South Wales 2006, Australia
| | - Fred Keijzer
- Department of Theoretical Philosophy, University of Groningen, Groningen, The Netherlands
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11
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Zhu F, Wang L, Wen Y, Yang L, Pan J, Wang Z, Wang W. Failure Handling of Robotic Pick and Place Tasks With Multimodal Cues Under Partial Object Occlusion. Front Neurorobot 2021; 15:570507. [PMID: 33762921 PMCID: PMC7982538 DOI: 10.3389/fnbot.2021.570507] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 01/29/2021] [Indexed: 11/13/2022] Open
Abstract
The success of a robotic pick and place task depends on the success of the entire procedure: from the grasp planning phase, to the grasp establishment phase, then the lifting and moving phase, and finally the releasing and placing phase. Being able to detect and recover from grasping failures throughout the entire process is therefore a critical requirement for both the robotic manipulator and the gripper, especially when considering the almost inevitable object occlusion by the gripper itself during the robotic pick and place task. With the rapid rising of soft grippers, which rely heavily on their under-actuated body and compliant, open-loop control, less information is available from the gripper for effective overall system control. Tackling on the effectiveness of robotic grasping, this work proposes a hybrid policy by combining visual cues and proprioception of our gripper for the effective failure detection and recovery in grasping, especially using a proprioceptive self-developed soft robotic gripper that is capable of contact sensing. We solved failure handling of robotic pick and place tasks and proposed (1) more accurate pose estimation of a known object by considering the edge-based cost besides the image-based cost; (2) robust object tracking techniques that work even when the object is partially occluded in the system and achieve mean overlap precision up to 80%; (3) contact and contact loss detection between the object and the gripper by analyzing internal pressure signals of our gripper; (4) robust failure handling with the combination of visual cues under partial occlusion and proprioceptive cues from our soft gripper to effectively detect and recover from different accidental grasping failures. The proposed system was experimentally validated with the proprioceptive soft robotic gripper mounted on a collaborative robotic manipulator, and a consumer-grade RGB camera, showing that combining visual cues and proprioception from our soft actuator robotic gripper was effective in improving the detection and recovery from the major grasping failures in different stages for the compliant and robust grasping.
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Affiliation(s)
- Fan Zhu
- Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
| | - Liangliang Wang
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, Hong Kong
| | - Yilin Wen
- Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
| | - Lei Yang
- Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
| | - Jia Pan
- Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
| | - Zheng Wang
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Wenping Wang
- Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
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12
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Chen X, Duanmu D, Wang Z. Model-Based Control and External Load Estimation of an Extensible Soft Robotic Arm. Front Robot AI 2021; 7:586490. [PMID: 33585572 PMCID: PMC7878371 DOI: 10.3389/frobt.2020.586490] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 12/14/2020] [Indexed: 11/19/2022] Open
Abstract
Soft robotics has widely been known for its compliant characteristics when dealing with contraction or manipulation. These soft behavior patterns provide safe and adaptive interactions, greatly relieving the complexity of active control policies. However, another promising aspect of soft robotics, which is to achieve useful information from compliant behavior, is not widely studied. This characteristic could help to reduce the dependence of sensors, gain a better knowledge of the environment, and enrich high-level control strategies. In this paper, we have developed a state-change model of a soft robotic arm, and we demonstrate how compliant behavior could be used to estimate external load based on this model. Moreover, we propose an improved version of the estimation procedure, further reducing the estimation error by compensating the influcence of pressure deadzone. Experiments of both methods are compared, displaying the potential effectiveness of applying these methods.
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Affiliation(s)
- Xiaojiao Chen
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Dehao Duanmu
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | - Zheng Wang
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
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13
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Zhang R, Shen Z, Zhong H, Tan J, Hu Y, Wang Z. A Cephalopod-Inspired Soft-Robotic Siphon for Thrust Vectoring and Flow Rate Regulation. Soft Robot 2020; 8:416-431. [PMID: 32758059 DOI: 10.1089/soro.2019.0152] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Cephalopods could simultaneously achieve both accurate positioning and agile bodily maneuvers by coordinating the mantle and the funnel, which is ideal for underwater robotic applications toward a compact propulsor with combined thrust vectoring and regulation. For a wide range of underwater applications from videography to manipulation, this novel approach would offer a compact and integrated alternative to the state-of-the-art with multiple vectoring thrusters. This article presents a biomimetic soft-robotic siphon (BSRS) as the propulsor unit, consisting of a novel central flow-regulative duct (CFRD) encircled by three circumferential siphon actuation muscles (SAMs). Hydraulic pressurization of the SAMs could enable both thrust vectoring by deflecting the BSRS and flow regulation by proportionally alternating the orifice of the CFRD. The design, modeling, and fabrication of the BSRS are presented in detail. Experiments using a prototype BSRS were conducted for validating the performances of deflection deformation and flow regulation, showing bending range of over 180° and flow-restricting capability of up to 100%. A burst effect was achieved with the ability of exceeding the constant flow rate by up to 50%, enabling tremendous thrust increase in very short time. This work proves the feasibility of combining omnidirectional deflection with flow regulation within a soft-robotic mechanism, paving the way to compact water-jetting propulsion for underwater robots.
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Affiliation(s)
- Runzhi Zhang
- Department of Mechanical Engineering and The University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Zhong Shen
- Department of Mechanical Engineering and The University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Hua Zhong
- Department of Mechanical Engineering and The University of Hong Kong, Hong Kong, Hong Kong SAR.,Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Jiyong Tan
- Department of Mechanical and Energy Engineering, SUSTECH-AISONO Joint Lab in Robotics, Southern University of Science and Technology, Shenzhen, China.,Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yong Hu
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Zheng Wang
- Department of Mechanical Engineering and The University of Hong Kong, Hong Kong, Hong Kong SAR.,Department of Mechanical and Energy Engineering, SUSTECH-AISONO Joint Lab in Robotics, Southern University of Science and Technology, Shenzhen, China.,Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
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14
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Gaudeni C, Pozzi M, Iqbal Z, Malvezzi M, Prattichizzo D. Grasping With the SoftPad, a Soft Sensorized Surface for Exploiting Environmental Constraints With Rigid Grippers. IEEE Robot Autom Lett 2020. [DOI: 10.1109/lra.2020.2983675] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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15
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Su Y, Fang Z, Zhu W, Sun X, Zhu Y, Wang H, Tang K, Huang H, Liu S, Wang Z. A High-Payload Proprioceptive Hybrid Robotic Gripper With Soft Origamic Actuators. IEEE Robot Autom Lett 2020. [DOI: 10.1109/lra.2020.2974438] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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