Route planning in a four-dimensional environment

Robots must be able to function in the real world. The real world involves processes and agents that move independently of the actions of the robot, sometimes in an unpredictable manner. A real-time integrated route planning and spatial representation system for planning routes through dynamic domains is presented. The system will find the safest most efficient route through space-time as described by a set of user defined evaluation functions. Because the route planning algorthims is highly parallel and can run on an SIMD machine in O(p) time (p is the length of a path), the system will find real-time paths through unpredictable domains when used in an incremental mode. Spatial representation, an SIMD algorithm for route planning in a dynamic domain, and results from an implementation on a traditional computer architecture are discussed

Assessment and learning outcomes: the evaluation of deep learning in an on-line course

Using an online learning environment, students from European countries collaborated and communicated to carry out problem based learning in occupational therapy. The effectiveness of this approach was evaluated by means of the final assessments and published learning outcomes. In particular, transcripts from peer-to-peer sessions of synchronous communication were analysed. The SOLO taxonomy was used and the development of deep learning was studied week by week. This allowed the quality of the course to be appraised and showed, to a certain extent, the impact of this online international course on the learning strategies of the students. Results indicate that deep learning can be supported by synchronous communication and online meetings between course participants.</p

A Cohesive Simulation and Testing Platform for Civil Autonomous Aerial Sensing and Operations

Drones (also known as sUAS or small Uncrewed Aerial Systems) are often flown with cameras to take images of an area of land. These images can then be used to create a map by stitching these images together. This map can then be analyzed using scientific principles to learn things about the land and make decisions or take action based on the information. The scientific application of drones is very advantageous, but flying a drone is inherently dangerous, impacting the safety of the airspace (particularly in the event of a crash), and drones are more dangerous the bigger they are. Smaller off-the-shelf drones are readily available to the public and are quite safe and easy to use. Larger near 55-lb fixed-wing mapping drones that can fly for 2.5 hours are quite costly and bring new risks into the equation. There are many barriers and risks to being able to successfully test equipment and to improving drone mapping technology. This research focuses on creating a simulator that can simulate the entire process of creating these scientific maps. Simulating a drone, a camera payload, and a world for the drone to fly over. By having a simulator, researchers will be able to test out new technologies without having to risk flying a drone or without having to overcome the challenges mentioned above. This research also focuses on creating a smaller simple camera payload that can be attached to a drone for performing test flights. This allows researchers to do scientific tests without risking flying larger systems. This work enables the testing of sUAS payload systems many times in the simulation and then, when the system works as it should, the test flights with an actual drone can commence. This reduces the amount of time it takes to develop scientific drone systems and reduces the risk of flight

Path Planning Through Time and Space in Dynamic Domains

Realistic robot problems involve navigating the robot through time as well as space. The obstacles that a robot must avoid and the pathways on which it travels are subject to changes throughout time. These changes can occur in a predictable or unpredictable fashion. This paper presents an integrated route planning and spatial representation system that allows paths to be calculated in dynamic domains. The path planner finds the "best route" through a given n-dimensional space. The "best route" is defined as the path through space-time with the best score as determined by a set of user-defined evaluatio

Resonant States in the Electronic Structure of the High Performance Thermoelectrics AgPbmSbTe_{m}SbTe_{2+m}$ ; The Role of Ag-Sb Microstructures

Ab initio electronic structure calculations based on gradient corrected density functional theory were performed on a class of novel quaternary compounds AgPb$_{m}SbTe$_{2+m}$, which were found to be excellent high temperature thermoelctrics with large figure of merit ZT ~2.2 at 800K. We find that resonant states appear near the top of the valence and bottom of the conduction bands of bulk PbTe when Ag and Sb replace Pb. These states can be understood in terms of modified Te-Ag(Sb) bonds. Electronic structure near the gap depends sensitively on the microstructural arrangements of Ag-Sb atoms, suggesting that large ZT values may originate from the nature of these ordering arrangements.Comment: Accepted in Physical Review Letter

Glass-Like Heat Conduction in High-Mobility Crystalline Semiconductors

The thermal conductivity of polycrystalline semiconductors with type-I clathrate hydrate crystal structure is reported. Ge clathrates (doped with Sr and/or Eu) exhibit lattice thermal conductivities typical of amorphous materials. Remarkably, this behavior occurs in spite of the well-defined crystalline structure and relatively high electron mobility ($\sim 100 cm^2/Vs$). The dynamics of dopant ions and their interaction with the polyhedral cages of the structure are a likely source of the strong phonon scattering.Comment: 4 pages, 3 postscript figures, to be published, Phys. Rev. Let

Integrating deliberative planning in a robot architecture

The role of planning and reactive control in an architecture for autonomous agents is discussed. The postulated architecture seperates the general robot intelligence problem into three interacting pieces: (1) robot reactive skills, i.e., grasping, object tracking, etc.; (2) a sequencing capability to differentially ativate the reactive skills; and (3) a delibrative planning capability to reason in depth about goals, preconditions, resources, and timing constraints. Within the sequencing module, caching techniques are used for handling routine activities. The planning system then builds on these cached solutions to routine tasks to build larger grain sized primitives. This eliminates large numbers of essentially linear planning problems. The architecture will be used in the future to incorporate in robots cognitive capabilites normally associated with intelligent behavior