A Two Dimensional Crystalline Atomic Unit Modular Self-reconfigurable Robot

Self-reconfigurable robots are designed so that they can change their external shape without human intervention. One general way to achieve such functionality is to build a robot composed of multiple, identical unit modules. If the modules are designed so that they can be assembled into rigid structures, and so that individual units within such structures can be relocated within and about the structure, then self-reconfiguration is possible. We propose the Crystalline Atomic unit modular self-reconfigurable robot, where each unit is called an Atom. In two dimensions, an Atom is square. Connectors at the faces of each Atom support structure formation (such structures are called Crystals). Centrally placed prismatic degrees of freedom give Atoms the ability to contract their outer side-length by a constant factor. By contracting and expanding groups of Atoms in a coordinated way, Atoms can relocate within and about Crystals. Thus Atoms are shown to satisfy the two properties necessary to function as modules of a self-reconfigurable robot. A powerful software simulator for Crystalline Atomic robots in two and three dimensions, called xtalsim, is presented. Xtalsim includes a high-level language interface for specifying reconfigurations, an engine which expands implicit reconfiguration plans into explicit Crystal state sequences, and an interactive animator which displays the results in a virtual environment. An automated planning algorithm for generating reconfigurations, called the Melt-Grow planner, is described. The Melt-Grow planner is fast (O(n2) for Crystals of n Atoms) and complete for a fully general subset of Crystals. The Melt-Grow planner is implemented and interfaced to xtalsim, and an automatically planned reconfiguration is simulated. Finally, the mechanics, electronics, and software for an Atom implementation are developed. Two Atoms are constructed and experiments are performed which indicate that, with some hardware improvements, an interesting self-reconfiguration could be demonstrated by a group of Atoms

Challenges in 3D Visualization for Mars Exploration Rover Mission

The Science Activity Planner (SAP), currently under development by our group at the Jet Propulsion Laboratory, will be the primary tool used for science data assessment and science activity planning during the Mars Exploration Rover (MER) mission. As part of its data visualization capability, SAP interactively displays 3D terrain surface data corresponding to the MER image data products. These datasets can be very large, e.g. on the order of tens of millions of vertices for a panorama, so it is a challenge to load and display them at interactive speeds on a workstation. We describe the software techniques we are implementing to address this challenge and present recent test results. A fundamental development is the new Visible Scalable Terrain (ViSTa) format, a flexible and precise interchange format for terrain data. Other developments include multi-threaded asynchronous event-driven data loading, practical heuristics for geometry LOD and texture resolution selection, multilevel garbage-collector friendly data caching, and an optimized ray intersection system

Distributed Operations for the Mars Exploration Rover Mission with the Science Activity Planner

Due to the length of the Mars Exploration Rover Mission, most scientists were unable to stay at the central operations facility at the Jet Propulsion Laboratory. This created a need for distributed operations software, in the form of the Distributed Science Activity Planner. The distributed architecture saved a considerable amount of money and increased the number of individuals who could be actively involved in the mission, contributing to its success

Three‐Dimensional Data Preparation and Immersive Mission‐Spanning Visualization and Analysis of Mars 2020 Mastcam‐Z Stereo Image Sequences

Abstract The Mars 2020 Mastcam‐Z stereo camera investigation enables the generation of three dimension (3D) data products needed to visualize and analyze rocks, outcrops, and other geological and aeolian features. The Planetary Robotics Vision Processing framework “PRoViP” as well as the Instrument Data System on a tactical—sol‐by‐sol—timeframe generate 3D vision products, such as panoramas, distance maps, and textured meshes. Structure‐from‐motion used by the Advanced Science Targeting Toolkit for Robotic Operations (ASTTRO) “Landform” tool and long baseline stereo pipelines add to the 3D vision products' suite on various scales. Data fusion with textured meshes from satellite imagery and 3D data analysis and interpretation of the resulting large 3D data sets is realized by visualization assets like the Planetary Robotics Vision 3D Viewer PRo3D, the 3D Geographical Information System GIS CAMP (Campaign Analysis Mapping and Planning tool), the ASTTRO 3D data presentation and targeting tool, and the Mastcam‐Z planning tool Viewpoint. The pipelines' workflows and the user‐oriented features of the visualization assets, shared across the Mars 2020 mission, are reported. The individual role and interplay, complements and synergies of the individual frameworks are explained. Emphasis is laid on publicly available 3D vision data products and tools. A representative set of scientific use cases from planetary geology, aeolian activity, soil analysis and impact science illustrates the scientific workflow, and public data deployment modes are briefly outlined, demonstrating that 3D vision processing and visualization is an essential mission‐wide asset to solve important planetary science questions such as prevailing wind direction, soil composition, or geologic origin

A pilot study to explore circulating tumour cells in pancreatic cancer as a novel biomarker

BACKGROUND: Obtaining tissue for pancreatic carcinoma diagnosis and biomarker assessment to aid drug development is challenging. Circulating tumour cells (CTCs) may represent a potential biomarker to address these unmet needs. We compared prospectively the utility of two platforms for CTC enumeration and characterisation in pancreatic cancer patients in a pilot exploratory study. PATIENTS AND METHODS: Blood samples were obtained prospectively from 54 consenting patients and analysed by CellSearch and isolation by size of epithelial tumour cells (ISET). CellSearch exploits immunomagnetic capture of CTCs-expressing epithelial markers, whereas ISET is a marker independent, blood filtration device. Circulating tumour cell expression of epithelial and mesenchymal markers was assessed to explore any discrepancy in CTC number between the two platforms. RESULTS: ISET detected CTCs in more patients than CellSearch (93% vs 40%) and in higher numbers (median CTCs/7.5 ml, 9 (range 0–240) vs 0 (range 0–144)). Heterogeneity observed for epithelial cell adhesion molecule, pan-cytokeratin (CK), E-Cadherin, Vimentin and CK 7 expression in CTCs may account for discrepancy in CTC number between platforms. CONCLUSION: ISET detects more CTCs than CellSearch and offers flexible CTC characterisation with potential to investigate CTC biology and develop biomarkers for pancreatic cancer patient management