14942562
Improving hallway navigation in mobile robots with sensor habituation
Habituation is a form of non-associative learning observed in a variety of species of animals. Arguably, it is the simplest form of learning. Nonetheless, the ability to habituate to certain stimuli implies plastic neural systems and adaptive behaviors. This article describes how computational models of habituation can be applied to real robots. In particular, we discuss the problem of the oscillatory movements observed when a Khepera robot navigates through narrow hallways. Results show that habituation to the proximity of the walls can lead to smoother navigation. Habituation to sensory stimulation to the sides of the robot does not interfere with the robot's ability to turn at dead ends and to avoid obstacles outside the hallway. This work shows that simple biological mechanisms of learning can be adapted to achieve better performance in real mobile robots.
33610290
Biomimetic Robotics
18983514
Sequence Learning in Mobile Robots Using Avalanche Neural Networks
This paper describes the implementation of a neural network for sequence learning that is based on a neurocomputational theory of learning. The network is implemented on a physical mobile robot in order to learn to reproduce sequences of motor actions. At the onset of a conditioned stimulus the robot is presented with a sequence of visual stimuli that produce reactive motor actions of different duration. Initial results show that after learning the robot can approximate the motor sequence with no visual stimulation.
14595145
An Approach to Vision-Based Person Detection in Robotic Applications
We present an approach to vision-based person detection in robotic applications that integrates top down template matching with bottom up classifiers. We detect components of the human silhouette, such as torso and legs; this approach provides greater invariance than monolithic methods to the wide variety of poses a person can be in. We detect borders on each image, then apply a distance transform, and then match templates at different scales. This matching process generates a focus of attention (candidate people) that are later confirmed using a trained Support Vector Machine (SVM) classifier. Our results show that this method is both fast and precise and directly applicable in robotic architectures.
39044537
Second-Order Conditioning in Mobile Robots
We have proposed a neural network that learns to control avoidance behaviors of a physical mobile robot through classical conditioning and operant conditioning. In this article we test whether our network can acquire second-order conditioning. During training we first associate the activation of the robot's infrared sensors with collisions. Then, the activation of a visual sensor is repeatedly paired with the activation of the infrared sensors. Results show that the robot learns to elicit avoidance responses whenever the visual sensor becomes active.
14995712
Applying Pattern Mining to Web Information Extraction
Information extraction (IE) from semi-structured Web documents is a critical issue for information integration systems on the Internet. Previous work in wrapper induction aim to solve this problem by applying machine learning to automatically generate extractors. For example, WIEN, Stalker, Softmealy, etc. However, this approach still requires human intervention to provide training examples. In this paper, we propose a novel idea to IE, by repeated pattern mining and multiple pattern alignment. The discovery of repeated patterns are realized through a data structure call PAT tree. In addition, incomplete patterns are further revised by pattern alignment to comprehend all pattern instances. This new track to IE involves no human effort and content-dependent heuristics. Experimental results show that the constructed extraction rules can achieves 97 percent extraction over fourteen popular search engines.
1871945
Specifications in software prototyping
Abstract We explore the use of software specifications for software prototyping. This paper describes a process model for software prototyping, and shows how specifications can be used to support such a process via a cellular mobile phone switch example.
40684547
Supporting event based traceability through high-level recognition of change events
Although requirements traceability is crucial in both the development and maintenance of a software system, traceability links and related artifacts tend to deteriorate, as time-pressured practitioners fail to systematically update them in response to change. Event-based traceability addresses this issue by establishing links through a loosely coupled publisher/subscriber scheme. Dependent entities subscribe to requirements and receive event notifications as changes occur. This paper focuses upon the role played by the requirements specification as a publisher of events. A set of standard change events is defined and a method for monitoring a user's actions within a requirements management environment and the subsequent recognition and publication of the change events is proposed. Early results obtained from testing this approach are reported.
1331907
An efficient representation of complex materials for real-time rendering
In this paper, we propose an appearance representation for general complex materials which can be applied in real-time rendering framework. By combining a single parametric shading function (such as the Phong model) and the proposed spatial-varying residual function (SRF), this representation can recover the appearance of complex materials with little loss of visual fidelity. The difference between the real data and the parametric shading is directly fitted by a specific function for easy reconstruction. It is simple, flexible and easy to be implemented on programmable graphics hardware. Experiments show that the mean square error (MSE) between the reconstructed appearance and real photographs is less than 5%.
43825190
Temporal Relations and Synchronization Agents
Temporal relationships, inevitable among distributed multimedia objects, require synchronization of multiple data streams in time. We propose using synchronization agents as "smart" distributed objects to deal with scheduling, integrating, and synchronizing distributed multimedia streams. A formal specification model, interoperable Petri nets, describes the agents' behavior and captures the temporal semantics existing among distributed multimedia objects.