Stable In-hand Manipulation for a Lightweight Four-motor Prosthetic Hand
🤖 AI Summary
This study addresses the limited stability of lightweight four-motor prosthetic hands when grasping objects of varying sizes and weights, particularly heavy items. The authors propose a closed-loop control strategy based on motor current feedback, integrated with an optimized single-axis thumb mechanism, to enable real-time estimation of object width and dynamic adjustment of the index finger position—facilitating adaptive in-hand manipulation without prior knowledge of object dimensions. This work presents the first application of current feedback for in-hand manipulation in lightweight prosthetic hands, significantly enhancing stability during heavy-object handling. The approach achieves 100% success in manipulating lightweight objects 5–30 mm wide and maintains ≥80% success with a 289 g aluminum prism—doubling the performance of non-coordinated control—and successfully executes daily tasks such as unscrewing bottle caps and holding a pen.
Application Category
📝 Abstract
Electric prosthetic hands should be lightweight to decrease the burden on the user, shaped like human hands for cosmetic purposes, and designed with motors enclosed inside to protect them from damage and dirt. Additionally, in-hand manipulation is necessary to perform daily activities such as transitioning between different postures, particularly through rotational movements, such as reorienting a pen into a writing posture after picking it up from a desk. We previously developed PLEXUS hand (Precision-Lateral dEXteroUS manipulation hand), a lightweight (311 g) prosthetic hand driven by four motors. This prosthetic performed reorientation between precision and lateral grasps with various objects. However, its controller required predefined object widths and was limited to handling lightweight objects (of weight up to 34 g). This study addresses these limitations by employing motor current feedback. Combined with the hand's previously optimized single-axis thumb, this approach achieves more stable manipulation by estimating the object's width and adjusting the index finger position to maintain stable object holding during the reorientation. Experimental validation using primitive objects of various widths (5-30 mm) and shapes (cylinders and prisms) resulted in a 100% success rate with lightweight objects and maintained a high success rate (>=80) even with heavy aluminum prisms (of weight up to 289 g). By contrast, the performance without index finger coordination dropped to just 40% on the heaviest 289 g prism. The hand also successfully executed several daily tasks, including closing bottle caps and orienting a pen for writing.
Problem
Research questions and friction points this paper is trying to address.
in-hand manipulation
prosthetic hand
object reorientation
stable grasping
lightweight design
Innovation
Methods, ideas, or system contributions that make the work stand out.
in-hand manipulation
current feedback
adaptive grasping
prosthetic hand
object reorientation
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