Soft sensor gives robots a better sense of touch
image:
Systematic overview of the humanoid dexterous hand with multi-degree-of-freedom posture perception. a The humanoid dexterous hand in various delicate operational scenarios. b The omnidirectional soft bending sensor in the humanoid dexterous hand.
view moreCredit: Microsystems & Nanoengineering
A new soft sensing system could help humanoid robots move their hands with far greater precision in delicate, human-like tasks. The study introduces a dexterous robotic hand equipped with omnidirectional bending sensors that can track both pitch and yaw at the finger joints, allowing the system to perceive complex finger posture in real time. By combining flexible sensing with a rigid-soft hand design, the researchers created a platform that not only moves more naturally but also performs demanding actions such as using scissors, operating a mouse, and playing the piano with improved control and stability.
Robotic hands have made major progress in grasping and pinching, but many still struggle with the finer motions that make the human hand so versatile. One key limitation is proprioception: while human fingers constantly sense their own position and movement, most humanoid hands remain weak at perceiving posture across multiple degrees of freedom. Existing soft sensors often detect only one bending mode or suffer from coupling problems when fingers flex and move sideways at the same time. This leaves a gap between robotic grasping and true dexterous manipulation. Based on these challenges, deeper research was needed into soft sensing systems capable of decoupling and accurately tracking multidirectional finger motion.
Researchers from Zhejiang University, Hangzhou Dianzi University, and Lishui University reported (DOI: 10.1038/s41378-026-01179-3) the work in Microsystems & Nanoengineering in 2026. The study presents a humanoid dexterous hand designed to solve a central problem in advanced robotics: how to give robot fingers a reliable sense of their own posture during complex motion. By embedding a new omnidirectional soft bending sensor into the hand, the team enabled real-time perception of both flexion and side-to-side movement in delicate manipulation tasks.
The hand features 18 active degrees of freedom and five rigid-flexible fingers, with each finger integrating a soft optical sensor built from segmented PMMA fibers, a trichromatic LED, and a chromatic detector. The design works by tracking how red, green, and blue light attenuate differently as the sensor bends. Because the fiber layout separates responses to pitch and yaw, the system can decouple the two motions instead of mixing them together. The paper reports strong repeatability over 100 cycles, with RMSE values of 2.1%, 1.9%, and 3.2% across the three optical channels. Under single bending, the average measurement error was only ±2.13° for pitch and ±2.34° for yaw. Crosstalk remained low: pure yaw contributed 3.2% to pitch, while pure pitch contributed 4.1% to yaw, with signal-to-crosstalk ratios of 50.68 dB and 30.81 dB, respectively. The team then moved beyond bench testing and demonstrated the hand in three visually compelling tasks—cutting with scissors, clicking a mouse, and playing piano keys—showing closed-loop posture control in actions that require subtle coordination rather than simple gripping.
The researchers suggest that the real advance is not just a new sensor, but a new way of giving robotic hands a more human-like internal awareness of motion. In their conclusion, they emphasize that the integrated rigid-soft design supports natural movement, while the sensing system delivers the stability, repeatability, and multi-DoF posture perception needed for complex operations. That combination could make future humanoid hands more capable in tasks where precision matters most.
This work points toward robotic hands that are not only stronger or faster, but more skillful. Better posture perception could improve humanoid robots used in service settings, industrial assembly, rehabilitation devices, and other environments where fingers must adapt to fragile or highly varied objects. The study’s demonstrations also hint at broader possibilities in human-robot interaction, where smoother and safer hand motion is essential. By showing that soft optical sensing can remain accurate while supporting complex multidirectional movement, the research moves robotic manipulation closer to the responsiveness and finesse of the human hand.
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References
DOI
Original Source URL
https://doi.org/10.1038/s41378-026-01179-3
Funding Information
This research was supported by the National Natural Science Foundation of China (No. 52475573), the Natural Science Foundation of Zhejiang Province (No. LTGY23E050002), the National Key Research and Development Program of China (No. 2023YFC2811500), the Science and Technology Innovation Project of the General Administration of Sport of China (24KJCX074), the Key Research and Development Programme of Zhejiang (No. 2024C03259, No. 2023C03196), and the Fundamental Research Funds for the Central Universities.
About Microsystems & Nanoengineering
Microsystems & Nanoengineering is an online-only, open access international journal devoted to publishing original research results and reviews on all aspects of Micro and Nano Electro Mechanical Systems from fundamental to applied research. The journal is published by Springer Nature in partnership with the Aerospace Information Research Institute, Chinese Academy of Sciences, supported by the State Key Laboratory of Transducer Technology.
Journal
Microsystems & Nanoengineering
Subject of Research
Not applicable
Article Title
Soft sensor for omnidirectional posture perception in humanoid dexterous hands
Magnetic tensegrity-enabled robotic gripper with adaptive energy barrier for UAV perching
Beijing Institute of Technology Press Co., Ltd
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(A) Perching behavior of biological and artificial systems. (B) Operational principle of our robotic gripper. (C) Energy variation of MTRG during operation. (D) Comparison of switching frequency f and force ratio κ between our paradigm and current bistable robotic grippers. Here, κ is defined as the ratio between failure force and triggering force. (E) Application demonstrations of our robotic gripper that is integrated into UAVs for implementing tasks such as grasping and perching, showing its potential for diverse scenarios.
view moreCredit: Lulu Han, Sun Yat-Sen University.
For long-endurance missions such as environmental monitoring and disaster response, UAVs remain fundamentally constrained by limited onboard energy because continuous lift generation is required during hovering. Perching on natural or artificial structures, such as branches or street lamps, has therefore been regarded as an effective means of extending mission duration by replacing sustained hovering with structurally supported resting. Although existing bioinspired perching systems have demonstrated attachment using robotic grippers, they typically require precise coordination between flight dynamics and grasping actuation, and many still depend on continuous or intermittent power input to maintain post-perching stability. In recent years, bistable grippers have emerged as a promising route toward reduced control complexity and energy consumption through passive engagement; however, in conventional bistable designs, the energy barrier is generally fixed once fabricated, making it difficult to reconcile compliant triggering with robust grasp retention. “While prior studies have explored tunable barriers using shape memory alloys or active actuators, such approaches still rely on external control and additional energy supply.” said the author Lulu Han, a researcher at Sun Yat-Sen University, “Therefore, the development of a perching gripper capable of passively achieving adaptive energy-barrier modulation is of considerable significance for improving the environmental adaptability, grasping stability, and energy efficiency of UAV perching systems, and holds promising application prospects.”
In this study, the authors developed a magnetic tensegrity-enabled bistable robotic gripper (MTRG), composed of two finger-like rigid frames hinged to a base, nonelastic cables, sliding supports, and neodymium magnets. The gripper maintains its initial stable state through the balance between magnetic attraction and cable tension, and undergoes rapid transition to a closed grasping state upon external triggering. To enable repeatable operation, an inflatable airbag and an elastic restoring element were further integrated into the base to actively reset the gripper after grasping. Methodologically, the authors first established a theoretical model based on the geometric configuration of the structure, and analyzed the effects of key geometric parameters, magnet spacing, magnetic force, and state-transition energy in order to determine a design region that balances triggering sensitivity and grasping stability. The system was then characterized through high-speed imaging and quasi-static mechanical testing to quantify closing dynamics, triggering force, and failure force. Finally, the gripper was integrated into a multirotor UAV platform together with an onboard pump, PWM control, sensing, and communication modules, followed by hovering-versus-perching energy tests, outdoor perching demonstrations, and UWB-based positioning experiments to evaluate its feasibility and performance in UAV perching applications.
The results demonstrate that the proposed MTRG establishes a strongly asymmetric energy barrier through nonlinear magnetic interaction: the transition from the initial state to the grasping state requires only about 0.58 J, whereas the reverse transition requires approximately 48.88 J, yielding an almost 85-fold difference. This enables rapid closure within about 42 ms while simultaneously combining low triggering force with high holding capability. Experimentally, the maximum triggering force was only about 0.15 N and remained stable over 1,000 cycles, whereas the failure force reached 25.38 N—approximately 200 times the triggering force. The holding performance was further enhanced by about 30% on rough surfaces, and the gripper was able to stably support payloads ranging from 0.45 to 2.07 kg. Although grasp stability decreased with increasing vibration frequency under dynamic disturbances, the system still showed meaningful environmental adaptability. In addition, the integrated airbag-based reset mechanism reliably recovered the bistable state at 28 kPa and, after optimization, enabled reset within about 15 s and deflation within about 20 s, substantially improving repeatable operation. When integrated into a UAV, the system further demonstrated reliable perching performance with negligible influence on flight behavior and attitude stability, thereby supporting its feasibility for low-energy perching and long-endurance aerial operations.
In summary, this study shows that a magnetic tensegrity-enabled bistable gripper can passively realize adaptive energy-barrier modulation, thereby combining compliant triggering and robust grasping within a single structural design, while enabling repeatable operation through an integrated airbag-based resetting module. When deployed on a UAV, the gripper demonstrates reliable perching across diverse scenarios, indicating that passive, physically intelligent grasping mechanisms may provide an effective route toward low-power, adaptive, and stable aerial perching. “More broadly, the work offers a new solution to the long-standing trade-off between sensitive triggering and secure retention in bistable grippers, and highlights the potential of magnetically actuated tensegrity mechanisms for long-duration deployment, high-altitude operation, and aerial robotic tasks in complex environments.” said Lulu Han.
Authors of the paper include Lulu Han, Hao Yang, Luobin Wang, Yuquan Zheng, Jingrui Yang, Yuxuan Fu, Jieliang Zhao, Zhong Wan, Zhigang Wu, Jie Zhang, and Jianing Wu.
This work was supported by the National Natural Science Foundation of China (grant nos. 62388101, T2422031, and 52275298), the China Postdoctoral Science Foundation (2025M781273), the Natural Science Foundation of Liaoning Province Program (2025080026-JH3/101), the Postdoctoral Fellowship Program of CPSF (GZC20240192), and the Fundamental Research Funds for the Central Universities (DUT25Z3209).
The paper, “Magnetic Tensegrity-Enabled Robotic Gripper with Adaptive Energy Barrier for UAV Perching” was published in the journal Cyborg and Bionic Systems on Mar 9, 2026, at https://doi.org/10.34133/cbsystems.0535.
Journal
Cyborg and Bionic Systems
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