A discriminative model for understanding natural language route directions

To be useful teammates to human partners, robots must be able to follow spoken instructions given in natural language. However, determining the correct sequence of actions in response to a set of spoken instructions is a complex decision-making problem. There is a "semantic gap" between the high-level symbolic models of the world that people use, and the low-level models of geometry, state dynamics, and perceptions that robots use. In this paper, we show how this gap can be bridged by inferring the best sequence of actions from a linguistic description and environmental features. This work improves upon previous work in three ways. First, by using a conditional random field (CRF), we learn the relative weight of environmental and linguistic features, enabling the system to learn the meanings of words and reducing the modeling effort in learning how to follow commands. Second, a number of long-range features are added, which help the system to use additional structure in the problem. Finally, given a natural language command, we infer both the referred path and landmark directly, thereby requiring the algorithm to pick a landmark by which it should navigate. The CRF is demonstrated to have 15% error on a held-out dataset, when compared with 39% error for a Markov random field (MRF). Finally, by analyzing the additional annotations necessary for this work, we find that natural language route directions map sequentially onto the corresponding path and landmarks 99.6% of the time. In addition, the size of the referred landmark varies from 0m[superscript 2] to 1964m[superscript 2] and the length of the referred path varies from 0m to 40.83m.United States. Office of Naval Research (MURIs N00014-07-1-0749

Compact routing for the future internet

The Internet relies on its inter-domain routing system to allow data transfer between any two endpoints regardless of where they are located. This routing system currently uses a shortest path routing algorithm (modified by local policy constraints) called the Border Gateway Protocol. The massive growth of the Internet has led to large routing tables that will continue to grow. This will present a serious engineering challenge for router designers in the long-term, rendering state (routing table) growth at this pace unsustainable. There are various short-term engineering solutions that may slow the growth of the inter-domain routing tables, at the expense of increasing the complexity of the network. In addition, some of these require manual configuration, or introduce additional points of failure within the network. These solutions may give an incremental, constant factor, improvement. However, we know from previous work that all shortest path routing algorithms require forwarding state that grows linearly with the size of the network in the worst case. Rather than attempt to sustain inter-domain routing through a shortest path routing algorithm, compact routing algorithms exist that guarantee worst-case sub-linear state requirements at all nodes by allowing an upper-bound on path length relative to the theoretical shortest path, known as path stretch. Previous work has shown the promise of these algorithms when applied to synthetic graphs with similar properties to the known Internet graph, but they haven't been studied in-depth on Internet topologies derived from real data. In this dissertation, I demonstrate the consistently strong performance of these compact routing algorithms for inter-domain routing by performing a longitudinal study of two compact routing algorithms on the Internet Autonomous System (AS) graph over time. I then show, using the k-cores graph decomposition algorithm, that the structurally important nodes in the AS graph are highly stable over time. This property makes these nodes suitable for use as the "landmark" nodes used by the most stable of the compact routing algorithms evaluated, and the use of these nodes shows similar strong routing performance. Finally, I present a decentralised compact routing algorithm for dynamic graphs, and present state requirements and message overheads on AS graphs using realistic simulation inputs. To allow the continued long-term growth of Internet routing state, an alternative routing architecture may be required. The use of the compact routing algorithms presented in this dissertation offer promise for a scalable future Internet routing system

Route schematization with landmarks

Predominant navigation applications make use of a turn-by-turn instructions approach and are mostly supported by small screen devices. This combination does little to improve users\u27 orientation or spatial knowledge acquisition. Considering this limitation, we propose a route schematization method aimed for small screen devices to facilitate the readability of route information and survey knowledge acquisition. Current schematization methods focus on the route path and ignore context information, specially polygonal landmarks (such as lakes, parks, and regions), which is crucial for promoting orientation. Our schematization method, in addition to the route path, takes as input: adjacent streets, point-like landmarks, and polygonal landmarks. Moreover, our schematic route map layout highlights spatial relations between route and context information, improves the readability of turns at decision points, and the visibility of survey information on small screen devices. The schematization algorithm combines geometric transformations and integer linear programming to produce the maps. The contribution of this paper is a method that produces schematic route maps with context information to support the user in wayfinding and orientation

Vector-based and landmark-guided navigation in desert ants inhabiting landmark-free and landmark-rich environments

Two species of desert ants – the North African Cataglyphis fortis and the central Australian Melophorus bagoti – differ markedly in the visual complexity of their natural habitats: featureless salt pans and cluttered, steppe-like terrain, respectively. Here we ask whether the two species differ in their navigational repertoires, in particular, whether in homing they place different emphasis on their vector-based and landmark-based routines. In trying to answer this question, we applied the same experimental paradigms to individual foragers of either species on either continent: training and/or testing with and/or without artificial landmark arrays. We found that the open-terrain species C. fortis runs off its (path integration) home vector much more readily even in unfamiliar landmark settings than the cluttered-terrain species M. bagoti. These data support the hypothesis that C. fortis has a higher propensity to rely on vector-mediated navigation, whereas in the same experimental situations M. bagoti more easily switches to landmark-guided behaviour. In the actual navigational performances, such species-specific propensities are most likely shaped by environment-dependent individual experiences

Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

Retrieving Landmark Salience Based on Wikipedia: An Integrated Ranking Model

Landmarks are important for assisting in wayfinding and navigation and for enriching user experience. Although many user-generated geotagged sources exist, landmark entities are still mostly retrieved from authoritative geographic sources. Wikipedia, the world’s largest free encyclopedia, stores geotagged information on many geospatial entities, including a very large and well-founded volume of landmark information. However, not all Wikipedia geotagged landmark entities can be considered valuable and instructive. This research introduces an integrated ranking model for mining landmarks from Wikipedia predicated on estimating and weighting their salience. Other than location, the model is based on the entries’ category and attributed data. Preliminary ranking is formulated on the basis of three spatial descriptors associated with landmark salience, namely permanence, visibility, and uniqueness. This ranking is integrated with a score derived from a set of numerical attributes that are associated with public interest in the Wikipedia page―including the number of redirects and the date of the latest edit. The methodology is comparatively evaluated for various areas in different cities. Results show that the developed integrated ranking model is robust in identifying landmark salience, paving the way for incorporation of Wikipedia’s content into navigation systems

RESOURCE ALLOCATION AND EFFICIENT ROUTING IN WIRELESS NETWORKS

In wireless networks, devices (nodes) are connected by wireless links. An important issue is to set up high quality (high bandwidth) and efficient routing paths when one node wants to send packets to other nodes. Resource allocation is the foundation to guarantee high quality connections. In addition, it is critical to handle void areas in order to set up detour-free paths. Moreover, fast message broadcasting is essential in mobile wireless networks. Thus, my research includes dynamic channel allocation in wireless mesh networks, geographic routing in Ad Hoc networks, and message broadcasting in vehicular networks. The quality of connections in a wireless mesh network can be improved by equip- ping mesh nodes with multi-radios capable of tuning to non-overlapping channels. The essential problem is how to allocate channels to these multi-radio nodes. We develop a new bipartite-graph based channel allocation algorithm, which can improve bandwidth utilization and lower the possibility of starvation. Geographic routing in Ad Hoc networks is scalable and normally loop-free. However, traditional routing protocols often result in long detour paths when holes exist. We propose a routing protocol-Intermediate Target based Geographic Routing (ITGR) to solve this problem. The novelty is that a single forwarding path can be used to reduce the lengths of many future routing paths. We also develop a protocol called Hole Detection and Adaptive Geographic Routing, which identifies the holes efficiently by comparing the length of a routing path with the Euclidean distance between a pair of nodes. We then set up the shortest path based on it. Vehicles play an important role in our daily life. During inter-vehicle communication, it is essential that emergency information can be broadcast to surrounding vehicles quickly. We devise an approach that can find the best re-broadcasting node and propagate the message as fast as possible