Three-dimensional scanner of a pipe with tilt detection

The 3D quantitative measurement system for a sewer pipe is introduced. Two parallel lasers are rotated by the motor and draw the two annular streaks on the inside surface of the pipe. The circular laser streaks are recorded by the CCD camera. The measurement of the cross-section is established by analyzing the recorded streaks. The tilt of the robot against the axis of the pipe is detected by the deviation between two parallel lasers. It enables us to measure the vertical cross section of the pipe regardless the tilt of the system to the pipe. Experimental result shows the feasibility of the system. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Robot populations and their controlled evolution

This paper reports recent results in controllability theory for a class of positive linear discrete-time systems which were employed to examine and analyse the reachability and controllability properties of cohort-type population models representing the dynamics of autonomous intelligent robot communities. This work was presented in part at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

Prowling autonomous mobile robot with a network camera

This research aimed to develop an autonomous mobile robot that helps various kinds of people. The evasion of obstacles is absolutely imperative so that the robot can act in a human-life environment. Therefore, we developed a robot that moves through doors and avoids obstacles with the help of images taken by a camera set on the robot. This work was presented in part at the 13th International Symposium on Artifical Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Timing control of the mobile robot using tau-margin

Recently, autonomous robots which are designed on the basis of biological mechanism have attracted much attention. In this paper, we focus on the mechanism of timing control studied by ecological psychology, and apply the framework to timing control of a mobile robot. Experiments using real robots have been conducted and effective behaviors have been realized. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

RISCBOT: A WWW-Enabled Mobile Surveillance and Identification Robot

This article describes RISCBOT (RISCBOT name has been derived from RISC lab and ‘bot’ of robot, a modular 802.11 b-enabled mobile autonomous robot built at the RISC lab of the University of Bridgeport. RISCBOT localizes itself and successfully fulfills www – enabled online user requests and navigates to various rooms, employing a visual recognition algorithm. This article describes the mechanical design, hardware and software algorithms of the robot, and the web-based interface for communicating with the robot. ^⋆RISC lab: Interdisciplinary Robotics, Intelligent Sensing and Control laboratory at the University of Bridgeport.     

A genetic approach to the design of autonomous agents for futures trading

We propose a genetic algorithm-based method for designing an autonomous trader agent. The task of the proposed method is to find an optimal set of fuzzy if–then rules that best represents the behavior of a target trader agent. A highly profitable trader agent is used as the target in the proposed genetic algorithm. A trading history for the target agent is obtained from a series of futures trading. The antecedent part of fuzzy if–then rules considers time-series data of spot prices, while the consequent part indicates the order of trade (Buy, Sell, or No action) with its degree of certainty. The proposed method determines the antecedent part of fuzzy if–then rules. The consequent part of fuzzy if–then rules is automatically determined from the trading history of the target trader agent. The autonomous trader agent designed by the proposed genetic algorithm consists of a fixed number of fuzzy if–then rules. The decision of the autonomous trader agent is made by fuzzy inference from the time-series data of spot prices. This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006     

Autonomous micro-robot “Kity” for maze contest

A table-look-up immune network is proposed to solve problems arising from autonomous microrobots trying to achieve a given goal with limited memory and calculation capacity. The method is implemented and tested with a microrobot “Kity”, with a size of less than 1 cubic inch. It is possible to generate enough rules to make the robot achieve the goal of navigating freely in a maze with a small number of sensors. Experimental results show the efficacy of immune networks in controling robots in restricted environments. Kity demonstrated the efficiency of the associated algorithm arrived at by winning first prize at the 4th and 5th International Microrobot Maze Contests held in Nagoya, Japan, in October, 1995 and 1996. This work was presented, in part, at the International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

A description of dynamic behavior of sensory/motor systems with fuzzy symbolic dynamic systems

This paper presents a model of continuous sensory/motor systems for autonomous agents in naviga-tion problems. The Markov environmental model and sequential plan are extended with fuzzy sets, which present the mathematical transformation from discrete state space to continuous state space. The extended fuzzy environmental model and fuzzy sequential knowledge allow the identification of continuous sensory/motor systems with a gradient descent-based parameter estimation algorithm. A simulation demonstrates the feasibility of the proposed method. This work was presented, in part, at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

Motion coordination algorithm for distributed agents in the cellular warehouse problem

A distributed approach is shown to coordinate the motions of transport tables for the cellular warehouse problem. In this approach, the tables are considered to be autonomous agents, and a built-in behavior function given by artificial neural networks (ANNs) and the evolved problem-oriented connection weights navigate the agents to their specified goals. To determine the agent to be moved, a measure of the priority to move is introduced. We show that distributed agents with the learned behavior function and the negotiation value perform a similar strategy to a “serializable” solution forN-puzzle problems, which provides a good heuristic strategy for large-scale problems. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001     

Auto-navigation of a wheelchair

This paper presents an autonomous wheelchair system with the capability of self-localization and obstacle avoidance. In our system, the ceiling lights are chosen as landmarks to realize the self-localization of the wheelchair, and a laser range-finder is used for obstacle avoidance. First the approaches of landmark recognition and selflocalization for the wheelchair are proposed. Then the principle of obstacle avoidance using a laser range-finder is described. Finally, the total system of the wheelchair is introduced and a navigational experiment is described. Experimental results indicate the effectiveness of our system. This work was presented, in part, at the International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

ANFIS-based approach for predicting sediment transport in clean sewer

The necessity of sewers to carry sediment has been recognized for many years. Typically, old sewage systems were designated based on self-cleansing concept where there is no deposition in sewer. These codes were applicable to non-cohesive sediments (typically storm sewers). This study presents adaptive neuro-fuzzy inference system (ANFIS), which is a combination of neural network and fuzzy logic, as an alternative approach to predict the functional relationships of sediment transport in sewer pipe systems. The proposed relationship can be applied to different boundaries with partially full flow. The present ANFIS approach gives satisfactory results (r² = 0.98 and RMSE = 0.002431) compared to the existing predictor.     

Supervised learning technique for a mobile robot controller in a visual line tracking task

This article deals with the development of learning methods for an intelligent control system for an autonomous mobile robot. On the basis of visual servoing, an approach to learning the skill of tracking colored guidelines is proposed. This approach utilizes a robust and adaptive image processing method to acquire features of the colored guidelines and convert them into the controller input. The supervised learning procedure and the neural network controller are discussed. The method of obtaining the learning data and training the neural network are described. Experimental results are presented at the end of the article. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001     

Design principles for autonomous agents: A case study of classification

Building artificial lifelike autonomous agents is still considered an art, rather than a science. A generally accepted precise methodology is missing, and—given the properties of the real world—it is doubtful whether such a methodology will ever be developed. Nevertheless, it is possible to define criteria and provide heuristics for good designs. We have developed a number of design principles which, when applied, lead to what we would consider good designs from a cognitive science or artificial life (ALife) perspective. The paper illustrates some of these principles using a case study of classification. Presented at the Internatial Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

Human-robot communication based on a mind model

We propose a mental image directed semantic theory (MIDST) and apply it to integrated multimedia information understanding, such as cross-media operations through intermediate knowledge representation. This article describes a multiagent model of the human mind based on the MIDST and its application to human–robot communication. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

Evolutionary robot controllers with competitive and cooperative neural networks

This article describes a new approach for control systems for an autonomous mobile robot by using sandwiches of two different types of neural network. One is a neural network with competition and cooperation, and is used for recognizing sensor information where synaptic coupling are fixed. The second is a neural network with adaptive synaptic couplings corresponding to a genotype in a creature, and used for self-learning for the wheel controls. In a computer simulation model, we were successful in obtaining four types of robot with good performance when going along a wall. The model also showed robustness in a real environment. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo Japan, January 15–17, 2001     

Synchrony in a self-repair network with a simple lattice

We investigate a synchrony in a self-repairing network of autonomous agents capable of repairing mutually. In this paper, we define two models: a synchronous model and asynchronous one. They differ in the timing when the agents change their state. Computer simulations revealed that the synchronous model has a critical point, while the asynchronous one does not. We also studied a repair scheme in asynchronous model where the repaired agents in turn repair neighbor agents successively in a chain-reactive fashion. Performance of the scheme has been examined by computer simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Development of distance recognition using an ocellus camera for an autonomous personal robot

We are attempting to develop an autonomous personal robot that has the ability to perform practical tasks in a human living environment by using information derived from sensors. When a robot operates in a human environment, the issue of safety must be considered in regard to its autonomous movement. Thus, robots absolutely require systems that can recognize the external world and perform correct driving control. We have thus developed a navigation system for an autonomous robot. The system requires only image data captured by an ocellus CCD camera. In this system, we allow the robot to search for obstacles present on the floor. Then, the robot obtains distance recognition necessary for evasion of the object, including data of the obstacle’s width, height, and depth by calculating the angles of images taken by the CCD camera. We applied the system to a robot in an indoor environment and evaluated its performance, and we consider the resulting problems in the discussion of our experimental results. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008