Iterative Temporal Motion Planning for Hybrid Systems in Partially Unknown Environments

This paper considers the problem of motion planning for a hybrid robotic system with complex and nonlinear dynamics in a partially unknown environment given a temporal logic specification. We employ a multi-layered synergistic framework that can deal with general robot dynamics and combine it with an iterative planning strategy. Our work allows us to deal with the unknown environmental restrictions only when they are discovered and without the need to repeat the computation that is related to the temporal logic specification. In addition, we define a metric for satisfaction of a specification. We use this metric to plan a trajectory that satisfies the specification as closely as possible in cases in which the discovered constraint in the environment renders the specification unsatisfiable. We demonstrate the efficacy of our framework on a simulation of a hybrid second-order car-like robot moving in an office environment with unknown obstacles. The results show that our framework is successful in generating a trajectory whose satisfaction measure of the specification is optimal. They also show that, when new obstacles are discovered, the reinitialization of our framework is computationally inexpensive

Expanding the solvent chemical space for self-assembly of dipeptide nanostructures.

Nanostructures composed of short, noncyclic peptides represent a growing field of research in nanotechnology due to their ease of production, often remarkable material properties, and biocompatibility. Such structures have so far been almost exclusively obtained through self-assembly from aqueous solution, and their morphologies are determined by the interactions between building blocks as well as interactions between building blocks and water. Using the diphenylalanine system, we demonstrate here that, in order to achieve structural and morphological control, a change in the solvent environment represents a simple and convenient alternative strategy to the chemical modification of the building blocks. Diphenylalanine (FF) is a dipeptide capable of self-assembly in aqueous solution into needle-like hollow micro- and nanocrystals with continuous nanoscale channels that possess advantageous properties such as high stiffness and piezoelectricity and have so emerged as attractive candidates for functional nanomaterials. We investigate systematically the solubility of diphenylalanine in a range of organic solvents and probe the role of the solvent in the kinetics of self-assembly and the structures of the final materials. Finally, we report the crystal structure of the FF peptide in microcrystalline form grown from MeOH solution at 1 Å resolution and discuss the structural changes relative to the conventional materials self-assembled in aqueous solution. These findings provide a significant expansion of the structures and morphologies that are accessible through FF self-assembly for existing and future nanotechnological applications of this peptide. Solvent mediation of molecular recognition and self-association processes represents an important route to the design of new supramolecular architectures deriving their functionality from the nanoscale ordering of their components.We thank the Newman Foundation (T.O.M., T.P.J.K.), the FEBS and the Tel Aviv University Center for Nanoscience and Nanotechnology (A.L.), the BBSRC (T.P.J.K.), and the Leverhulme Trust and Magdalene College (A.K.B.) for financial support. A.L. thanks Or Berger for his assistance with the HR-SEM imaging. The X-ray diffraction data collection experiments were performed in the crystallographic X-ray facility at the Department of Biochemistry, University of Cambridge. The authors thank Pavel Afonin for help with PHENIX software suite in the refinement of the structures.This is the accepted manuscript for a paper published in ACS Nano, 2014, 8 (2), pp 1243–1253 DOI: 10.1021/nn404237f , Publication Date (Web): January 14, 201

Super-resolution far-field ghost imaging via compressive sampling

Much more image details can be resolved by improving the system's imaging resolution and enhancing the resolution beyond the system's Rayleigh diffraction limit is generally called super-resolution. By combining the sparse prior property of images with the ghost imaging method, we demonstrated experimentally that super-resolution imaging can be nonlocally achieved in the far field even without looking at the object. Physical explanation of super-resolution ghost imaging via compressive sampling and its potential applications are also discussed.Comment: 4pages,4figure