Human-Inspired Grasp Control in Robotics 2025
A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Locomotion and Bioinspired Robotics".
Deadline for manuscript submissions: 15 December 2025 | Viewed by 364
Special Issue Editor
Interests: mechanism design; robotic system and technology; biomechatronics; complex system modeling and control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Humans have a remarkable ability to grasp and manipulate various objects. This Special Issue, entitled “Human-Inspired Grasp Control in Robotics 2025”, tackles the challenge of enabling robots to efficiently and intuitively manipulate objects in real-world scenarios. The objective is to replicate the way humans handle objects in order to enhance the adaptability and dexterity of robotic systems. This research holds practical implications for fields such as prosthetics, manufacturing, healthcare, and household robotics, where precise and flexible object manipulation is crucial.
Traditional approaches to grasping control in robotics rely on rigid grasping models that struggle to cope with the dynamic nature of real-world environments. To address this drawback, researchers propose a human-inspired approach that draws inspiration from how humans utilize tactile sensing and feedback to adjust their grip on objects. This approach comprises key elements such as tactile sensing, object recognition, adaptive planning algorithms, and so on. It can empower the robot to adapt its grip based on the unique characteristics of an object and environmental constraints, ultimately enhancing grasp stability and success rates. It underscores the significance of emulating human grasping strategies in order to elevate the adaptability and dexterity of robotic systems. The proposed techniques hold immense potential for advancing robotic manipulation capabilities across a wide array of practical real-world tasks.
Dr. Yi Zhang
Guest Editor
Manuscript Submission Information
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Keywords
- human-inspired grasping
- reinforcement learning
- tactile sensing
- object recognition
- force control
- position control
- robotic grasping
- robot–environment interaction
- dexterous grasping
- grasp posture
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Related Special Issue
- Human-Inspired Grasp Control in Robotics in Biomimetics (8 articles)
