Grounding Verbs of Motion in Natural Language Commands to Robots

To be useful teammates to human partners, robots must be able to follow spoken instructions given in natural language. An important class of instructions involve interacting with people, such as “Follow the person to the kitchen” or “Meet the person at the elevators.” These instructions require that the robot fluidly react to changes in the environment, not simply follow a pre-computed plan. We present an algorithm for understanding natural language commands with three components. First, we create a cost function that scores the language according to how well it matches a candidate plan in the environment, defined as the log-likelihood of the plan given the command. Components of the cost function include novel models for the meanings of motion verbs such as “follow,” “meet,” and “avoid,” as well as spatial relations such as “to” and landmark phrases such as “the kitchen.” Second, an inference method uses this cost function to perform forward search, finding a plan that matches the natural language command. Third, a high-level controller repeatedly calls the inference method at each timestep to compute a new plan in response to changes in the environment such as the movement of the human partner or other people in the scene. When a command consists of more than a single task, the controller switches to the next task when an earlier one is satisfied. We evaluate our approach on a set of example tasks that require the ability to follow both simple and complex natural language commands. Keywords: Cost Function; Spatial Relation; State Sequence; Edit Distance; Statistical Machine TranslationUnited States. Office of Naval Research (Grant MURI N00014-07-1-0749

Toward understanding natural language directions

Speaking using unconstrained natural language is an intuitive and flexible way for humans to interact with robots. Understanding this kind of linguistic input is challenging because diverse words and phrases must be mapped into structures that the robot can understand, and elements in those structures must be grounded in an uncertain environment. We present a system that follows natural language directions by extracting a sequence of spatial description clauses from the linguistic input and then infers the most probable path through the environment given only information about the environmental geometry and detected visible objects. We use a probabilistic graphical model that factors into three key components. The first component grounds landmark phrases such as "the computers" in the perceptual frame of the robot by exploiting co-occurrence statistics from a database of tagged images such as Flickr. Second, a spatial reasoning component judges how well spatial relations such as "past the computers" describe a path. Finally, verb phrases such as "turn right" are modeled according to the amount of change in orientation in the path. Our system follows 60% of the directions in our corpus to within 15 meters of the true destination, significantly outperforming other approaches.United States. Office of Naval Research (MURI N00014-07-1-0749

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

An electrophysiological study of putative neurotransmitters and histochemical localisation of biogenic amines in the central nervous system of the cockroach 'Periplanea Americana'

A modification of the fluorescent histochemical glyoxylic acid (GA) method was used for localization of biogenic amines in wholemount ventral nerve cord and suboesophageal ganglia of the cockroach, Periplaneta americana. The distributions of fluorescent neurone somata within each ganglion and of nerve processes within the ganglia, interganglionic connectives and peripheral nerves were determined. An assessment was made of the effects of colchicine, nialamide plus DOPA and reserpine on the specific tissue fluorescence. The available evidence suggests that most of the specific fluorescence is due to dopamine. Infusion of hexamminecobaltic chloride was used to identify which fluorescent neurone pairs in the prothoracic and suboesophageal ganglia projected into the interganglionic connnectives and peripheral nerves. In order to determine the detailed morphology of certain of the fluorescent neurones GA was combined with intracellular injection of either Lucifer Yellow, hexamminecobaltic chloride, or Horseradish peroxidase. Technical difficulties, however, were encountered with the identification and filling of the neurones. A prothoracic neurone was identified which depolarized in response to pressure ejected and bath applied dopamine and noradrenaline. Both phentolamine and propranolol reversibly inhibited the dopamine response, although these drugs were also effective at antagonizing the cell's response to acetylcholine. Bath application of the drugs forskolin, IBMX and dibutyryl cyclic AMP provided evidence that in this case dopamine does not act through the second messenger, cyclic AMP. Additional electrophysiological experiments determined the effect of pressure ejected application of glutamate and GABA upon the electrical response of an identified metathoracic motoneurone. Picrotoxin reversibly inhibited the amino acid responses. Long term application of both picrotoxin and 4-acetamido-4' -isothiocyanostilbene-2,2'-disulphonic acid (SITS) produced changes in the membrane properties of the neurone such that the neurone somata became able to actively support action potentials

La prévention de l'hypoglycémie associée à l’activité physique chez les adultes vivant avec le diabète de type 1

Problématique : La pratique d’activité physique devrait être encouragée chez les individus avec le diabète de type 1 (DbT1), mais est limitée par la crainte de l'hypoglycémie. Les personnes traitées avec la pompe à insuline peuvent réduire temporairement la perfusion d’insuline basale. Pour un exercice à distance du repas, il s’agit de la méthode privilégiée pour prévenir l’hypoglycémie induite par l’exercice, mais aucune étude n’a validé le moment optimal pour le faire. Objectif : Comparer l’efficacité de trois moments de réduction du débit de base d’insuline de 80%, soit au moment de débuter (T0), 20 minutes (T-20) ou 40 minutes (T-40) avant un exercice de 45 minutes sur vélo stationnaire d’intensité moyenne (60%VO2peak) pratiqué 3 heures après un repas standardisé. Résultats : Aucune différence entre les stratégies quant au pourcentage du temps 4,0 mmol/L et au temps passé entre 4,0-10,0 mmol/L n’a été observée. Avec T-40, quoique non significatif, la glycémie de départ était plus élevée, moins de participants ont eu besoin de consommer des glucides avant et pendant l’exercice et le délai avant l’apparition de l’hypoglycémie était plus long en comparaison avec T0 et T-20. Conclusion : Chez les personnes avec le DbT1 et traitées par pompe à insuline, la réduction de 80% du débit basal d’insuline 40 minutes avant un exercice de 45 minutes d’intensité moyenne effectué à distance du repas n’est pas suffisante pour réduire l’hypoglycémie. D’autres études sont requises pour déterminer si cette réduction devrait être plus importante, plus hâtive ou combinée à un apport en glucides.Rational : For its benefits, physical activity should be encouraged in individuals living with type 1 diabetes (T1D) but is limited by the fear of hypoglycemia. People treated with continuous subcutaneuous insulin infusion (insulin pump) have the option to temporarily reduce basal insulin infusion rate. For an exercise practiced in the late post-prandial phase, this is the preferred method for preventing exercise-induced hypoglycemia, but no study has validated the optimal timing to reduce basal insulin infusion. Objective: To compare the efficacy of three timings to decrease basal insulin infusion rate by 80%, either at the start (T0), 20 minutes (T-20), or 40 minutes (T-40) before a 45-min exercise on a stationary bicycle at moderate intensity (60% VO2peak) performed 3 hours after a standardized meal. Results: No significant difference between the three strategies in terms of percentage of time spent under 4.0 mmol/L and time spent between 4.0 and 10.0 mmol/L was observed. With a reduction at T-40, although not significant, the glucose level at exercise onset was higher, fewer participants needed additional carbohydrates before and during exercise, and the time to first hypoglycemia was longer in comparison with T0 and T-20. Conclusion: In people living with T1D and treated with an insulin pump, an 80% reduction in basal insulin infusion 40 minutes before a 45-min moderate intensity exercise practiced in a late post-prandial state is not enough to reduce hypoglycemia. Further studies are needed to determine whether this reduction should be greater, earlier and/or combined with carbohydrates

Prompt Upsilon and Psi Production at LEP

Color-octet contributions to quarkonia production at LEP are studied herein. The short distance formation of heavy quark-antiquark pairs in color-octet configurations via gluon fragmentation processes is significantly enhanced relative to the creation of color-singlet pairs via heavy quark fragmentation. But the subsequent long distance hadronization of these colored pairs into physical quarkonium bound states is suppressed compared to the nonperturbative evolution of their colorless counterparts. We find that the overall LEP rates for gluon fragmentation into prompt Upsilon and Psi vector bosons exceed those from heavy quark fragmentation. Inclusion of the dominant color-octet quarkonium production channel eliminates sizable discrepancies between previous predictions and recent measurements of prompt Z \to \Jpsi+X, $Z \to \psi'+X$ and $Z \to \Upsilon+X$ branching fractions.Comment: 15 pages, harvmac, 3 uuencoded figure

Sharing and visualizing environmental data using Virtual Globes

Virtual globe technology holds many exciting possibilities for environmental science. These easy-to-use, intuitive systems provide means for simultaneously visualizing four-dimensional environmental data from many different sources, enabling the generation of new hypotheses and driving greater understanding of the Earth system. Through the use of simple markup languages, scientists can publish and consume data in interoperable formats without the need for technical assistance. In this paper we give, with examples from our own work, a number of scientific uses for virtual globes, demonstrating their particular advantages. We explain how we have used Web Services to connect virtual globes with diverse data sources and enable more sophisticated usage such as data analysis and collaborative visualization. We also discuss the current limitations of the technology, with particular regard to the visualization of subsurface data and vertical sections

Human perceptions of artificial surfaces for field hockey

Measuring the performance of a sports surface is typically derived from a series of field and laboratory tests that assess the playing properties under simulated game conditions. However, from a player’s perspective their own comfort and confidence in the surface and its playing characteristics are equally if not more important. To date no comparative study to measure playing preference tests has been made. The aim of this research was to develop a suitable method for eliciting player perceptions of field hockey pitches and determine the key themes that players consider when assessing field hockey pitches. To elicit meaningful unbiased human perceptions of a playing surface, an individual subjective analysis was carried out, using interviews and inductive analysis of the recorded player statements. A qualitative analysis of elite hockey players (n = 22) was performed to obtain their perceptions immediately after a competitive match. The significant surface characteristics that emerged as part of an inductive analysis of their responses were grouped together and formed five general themes or dimensions: player performance, playing environment, pitch properties, ball interaction and player interaction. Each dimension was formed from a hierarchy of sub-themes. During the analysis, relationships between the dimensions were identified and a structured relationship model was produced to highlight each relationship. Players’ responses suggested that they perceived differences between pitches and that the majority of players considered a ‘hard’ pitch with a ‘low’ ball bounce facilitating a ‘fast’ game speed was desirable. However, further research is required to understand the relative importance of each theme and to develop appropriate measurement strategies to quantify the relevant engineering properties of pitch materials

Color-Octet Fragmentation and the psi' Surplus at the Tevatron

The production rate of prompt $\psi'$'s at large transverse momentum at the Tevatron is larger than theoretical expectations by about a factor of 30. As a solution to this puzzle, we suggest that the dominant $\psi'$ production mechanism is the fragmentation of a gluon into a $c \bar c$ pair in a pointlike color-octet S-wave state, which subsequently evolves nonperturbatively into a $\psi'$ plus light hadrons. The contribution to the fragmentation function from this process is enhanced by a short-distance factor of $1/\alpha_s^2$ relative to the conventional color-singlet contribution. This may compensate for the suppression by $v^4$, where $v$ is the relative momentum of the charm quark in the $\psi'$. If this is indeed the dominant production mechanism at large $p_T$, then the prompt $\psi'$'s that are observed at the Tevatron should almost always be associated with a jet of light hadrons.Comment: 9 pages, LaTe

Understanding natural language commands for robotic navigation and mobile manipulation

This paper describes a new model for understanding natural language commands given to autonomous systems that perform navigation and mobile manipulation in semi-structured environments. Previous approaches have used models with fixed structure to infer the likelihood of a sequence of actions given the environment and the command. In contrast, our framework, called Generalized Grounding Graphs, dynamically instantiates a probabilistic graphical model for a particular natural language command according to the command's hierarchical and compositional semantic structure. Our system performs inference in the model to successfully find and execute plans corresponding to natural language commands such as "Put the tire pallet on the truck." The model is trained using a corpus of commands collected using crowdsourcing. We pair each command with robot actions and use the corpus to learn the parameters of the model. We evaluate the robot's performance by inferring plans from natural language commands, executing each plan in a realistic robot simulator, and asking users to evaluate the system's performance. We demonstrate that our system can successfully follow many natural language commands from the corpus