🤖 AI Summary
Underactuated grippers face a fundamental trade-off between geometric adaptability and frictional safety during dynamic manipulation of multi-size objects. Method: This paper proposes a friction-aware, potential-field-driven design and control framework. It pioneers the integration of the Coulomb friction model into potential-field analysis, revealing the critical role of dynamically adjustable geometric parameters—palm width, link length, and transmission ratio—in achieving stable caging (beyond force-feedback control alone). A tendon-pulley mechanism enables real-time, concurrent adaptation of these three parameters, while stability is guaranteed via friction-constrained analytical criteria—without increasing sensor complexity. Contribution/Results: The framework significantly enhances safe grasping and in-hand rotational/translational manipulation across diverse object sizes. Experiments demonstrate superior performance over fixed-geometry + force-control baselines on custom manipulation metrics.
📝 Abstract
In this paper we present a potential energy map based approach that provides a framework for the design and control of a robotic grasper. Unlike other potential energy map approaches, our framework considers friction for a more realistic perspective on grasper performance. Our analysis establishes the importance of considering dynamically variable geometry in grasper design, namely palm width, link lengths, and transmission ratios, which are assumed to be able to change in real-time. Our analysis assumes a two-phalanx tendon-pulley underactuated grasper, but it can be extended to other underactuated mechanisms. We demonstrate the utility of these novel potential energy maps and the method used to generate them in order by showing how various design parameters impact the grasping and in-hand manipulation performance of a particular design across a range of object sizes and friction coefficients. Optimal grasping designs have palms that scale with object size and transmission ratios that scale with the coefficient of friction. Using a custom in-hand manipulation metric, we compared the in-hand manipulation capabilities of a grasper that only dynamically varied its palm size, link lengths, and transmission ratios to a grasper with a variable palm and controllable actuation efforts. The analysis revealed the advantage of dynamically variable geometry; by varying only its palm size, link lengths, and transmission ratios in real-time, safe, caged in-hand manipulation of a wide range of objects could be performed.
