Knot-inspired optical sensors for slip detection and friction measurement in dexterous robotic manipulation

Friction plays a critical role in dexterous robotic manipulation.However,realizing friction sensing remains a challenge due to the difficulty in designing sensing structures to decouple multi-axial forces.Inspired by the topological mechanics of knots,we construct optical fiber knot(OFN)sensors for slip detection and friction measurement.By introducing localized self-contacts along the fiber,the knot structure enables anisotropic responses to normal and frictional forces.By employing OFNs and a change point detection algorithm,we demonstrate adaptive robotic grasping of slipping cups.We further develop a robotic finger that can measure tri-axial forces via a centrosymmetric architecture composed of five OFNs.Such a tactile finger allows a robotic hand to manipulate human tools dexterously.This work could provide a straightforward and cost-effective strategy for promoting adaptive grasping,dexterous manipulation,and human-robot interaction with tactile sensing.

Rigid-Soft Coupled Robotic Gripper for Adaptable Grasping

Inspired by the morphology of human fingers,this paper proposes an underactuated rigid-soft coupled robotic gripper whose finger is designed as the combination of a rigid skeleton and a soft tissue.Different from the current grippers who have multi-point contact or line contact with the target objects,the proposed robotic gripper enables surface contact and leads to flexible grasping and robust holding.The actuated mechanism,which is the palm of proposed gripper,is optimized for excellent operability based on a mathematical model.Soft material selection and rigid skeleton structure of fingers are then analyzed through a series of dynamic simulations by RecurDyn and Adams.After above design process including topology analysis,actuated mechanism optimization,soft material selection and rigid skeleton analysis,the rigid-soft coupled robotic gripper is fabricated via 3D printing.Finally,the grasping and holding capabilities are validated by experiments testing the stiffness of a single finger and the impact resistance of the gripper.Experimental results show that the proposed rigid-soft coupled robotic gripper can adapt to objects with different properties(shape,size,weight and softness)and hold them steadily.It confirms the feasibility of the design procedure,as well as the compliant and dexterous grasping capabilities of proposed rigid-soft coupled gripper.

A GRASP Algorithm for Multi-objective Circuit Partitioning

Circuit partitioning plays a crucial role in very large-scale integrated circuit (VLSI) physical design automation. With current trends, partitioning with multiple objectives which includes cutsize, area, delay, and power obtains much concentration. In this paper, a multi-objective greedy randomized adaptive search procedure (GRASP) is presented for simultaneous cutsize and circuit delay minimization. Each objective is assigned a preference or weight to direct the search procedure and generate a variety of efficient solutions by changing the preference. To get a good initial partition with minimal cutsize and circuit delay, the gain of each module in a circuit is computed by considering both signal nets and circuit delay. The performance of the proposed algorithm is evaluated on a standard set of partitioning benchmark. The experimental results show that the proposed algorithm can generate a set of Pareto optimal solutions and is efficient for tackling multi-objective circuit partitioning.

On Adaptive Grasp with Underactuated Anthropomorphic Hands

To automatically adapt to the shape of different objects with enough grasping force is a challenge in the design of under- actuated anthropomorphic hands, because the grasped object is easily ejected from the hands during underactuated grasping process. The goal of this paper is to develop a design method of underactuated anthropomorphic hands to guarantee reliable adaption to different grasped objects. An analysis method is developed to investigate the evolution of motion and force in the whole underactuated grasping process. Based on the evolution of motion and force, the underactuated grasping process is decomposed into four aspects including initial contact state, grasp terminal state, grasp trajectory and rate of progress. More- over, the influence factors of such four aspects are found as the form of the combinations of underactuated mechanism pa- rameters. According to the four aspects of the underactuated grasping process, this paper presents a stepwise parameter design method through optimization of parameter combinations step-by-step. The reliable adaptive grasp for a wide scale of grasped object size is achieved. Experimental setups are constructed to corroborate the results from the theory analysis and design.

Humanoid Design of Mechanical Fingers Using a Motion Coupling and Shape-adaptive Linkage Mechanism

This paper proposes a novel underactuated finger mechanism based on a motion coupling and shape-adaptive linkage design that combines anthropomorphic free motion and adaptive grasping. The proposed three-joint finger mechanism with one active Degree of Freedom （DOF） consists of a five-linkage meehanism in the proximal phalanx and a mechanism comprising two parallel planar four-bar linkages in the middle phalanx. The respective mechanism allows the simultaneously rotation of their corresponding pha- langes in the plane before making contact with an object, and can fully envelop an object, even if certain phalanges are blocked. The duel parallel four-bar linkage mechanism is adopted to improve the grasping capacity of the distal phalanx. An optimal design of the finger is presented according to anthropomorphic phalanx trajectories and maximized grasping forces obtained with consideration for the angular velocity relationships of the three phalanges and their force transmission performances. The functionality of the proposed finger mechanism is verified through multiple simulations and grasping experiments using a prototype finger.