Missing traces affect the result of subsequent steps, such as migration and amplitude versus offset (AVO) analysis, which harms the understanding of the subsurface structure and hydrocarbon exploration. Framelet transform can sparsely represent seismic data and it can describe data in detail. Compared with the commonly used$l_{1}$norm,$l_{p}$quasi-norm has higher sparsity. In this letter, we establish a new subject with$l_{p}$quasi-norm and framelet transform to reconstruct the seismic record. Instead of a conventional solver, we apply the alternating direction method of multiplier (ADMM) to solve the problem. Both synthetic test and field application prove that our proposed method not only gets a good result with high signal-noise-ratio (SNR) but also costs much less time than the conventional method. This indicates that the interplay of framelet transform and$l_{p}$quasi-norm can do a good job in seismic data reconstruction.

Dextrous manipulation is a fundamental problem in the study of multifingered robotic hands. Given a robotic hand and an object to be manipulated by the hand in an environment filled with obstacles, the main objectives of dextrous manipulation are to have the hand grasp the object and transfer it from a start configuration to a goal configuration without collision. To fulfill such a task in general, we will need: (a) a manipulation planner to generate a feasible path for the hand; and (b) a controller to implement the planned path. In this overview paper, we define the manipulation planning problem and present a unified control system architecture for multifingered manipulation (CoSAM/sup 2/). By incorporating the various kinematic and static relationships of a multifingered robotic hand system with proper sensory data inputs at different stages, CoSAM/sup 2/ achieves the various objectives of dextrous manipulation. Theoretical background of the control system design along with real-time experimental results are described.

In this paper, we propose a unified control system architecture for multifingered manipulation (CoSAM/sup 2/). CoSAM/sup 2/ achieves simultaneously three objectives of multifingered manipulation: (a) Motion trajectory (velocity/force) tracking of a grasped object; (b) Improving the grasp configuration in the course of object manipulation; and (c) Optimizing grasping forces to enforce contact constraint and compensate for external object wrenches. CoSAM/sup 2/ is organized in a modular and hierarchic structure so that each module implements a specified function using inputs from its predecessors and a minimum number of sensory data signals. CoSAM/sup 2/ is also flexible in accommodating addition of new modules. Here, we give the details for the coordinated motion generation module and the grasping force generation module.