Top PDF Behavioural strategy for indoor mobile robot navigation in dynamic environments

Behavioural strategy for indoor mobile robot navigation in dynamic environments

Behavioural strategy for indoor mobile robot navigation in dynamic environments

Development of behavioural strategies for indoor mobile navigation has become a challeng- ing and practical issue in a cluttered indoor environment, such as a hospital or factory, where there are many static and moving objects, including humans and other robots, all of which trying to complete their own specific tasks; some objects may be moving in a similar direction to the robot, whereas others may be moving in the opposite direction. The key requirement for any mobile robot is to avoid colliding with any object which may prevent it from reaching its goal, or as a consequence bring harm to any individual within its workspace. This chal- lenge is further complicated by unobserved objects suddenly appearing in the robots path, particularly when the robot crosses a corridor or an open doorway. Therefore the mobile robot must be able to anticipate such scenarios and manoeuvre quickly to avoid collisions. In this project, a hybrid control architecture has been designed to navigate within dynamic environments. The control system includes three levels namely: deliberative, intermediate and reactive, which work together to achieve short, fast and safe navigation. The deliberative level creates a short and safe path from the current position of the mobile robot to its goal using the wavefront algorithm, estimates the current location of the mobile robot, and ex- tracts the region from which unobserved objects may appear. The intermediate level links the deliberative level and the reactive level, that includes several behaviours for implementing the global path in such a way to avoid any collision.
Show more

204 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

The data temperature mark strategy is relatively a new phenomenon, which categorizes data block accessibility for general task processing [21] [22] [23] [24]. Initially, this concept was introduced by Rohith Subramanyam [25] and later Apache Hadoop adopted with few changes in their architecture [10]. Moreover, many researchers presented their approaches to optimize temperature marked data block accessibility. Jianjiang Li [26] uses data temperature property to back up hot data blocks through an encoding decoding compression

7 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Methods: during this study there were used pedagogical studies’ methods, such as study analysis on theme, methods of theoretical comparison and generalization, studying international experience, questioning. Findings: Academic cloud storages were developed by authors, which nowadays are realized by local network, but further are planned with internet access. For realization were analyzed cloud solutions and development strategy of IT-system for Kazakhstan universities on this issue. On work were described designed cloud storages, were provided practical and methodical guidance for its usage, which are convenient for students. In article reviewed and evaluated the benefits of developing and using cloud storage in educational process on training of future teachers of computer science, as well as practical recommendations given for realization of cloud technologies on educational process in universities.
Show more

8 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Some expressions created at the coverage level mentioned above may not be satisfactory, and if many combinations are not satisfactory for example, using a thorough strategy, the constraint solver consumes a lot of unnecessary runtimes. For this purpose, one general expression is formulated that covers how many invariants should be considered, and where some of them may be invalidated but not precisely specified. If the condition solver locates satisfactory tasks, then this tasks can infer from the constraint not only the model but also the invariant constructions considered in the invariant.
Show more

11 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

The composite nonlinear feedback (CNF) control is applied as a new control strategy for yaw rate tracking controller in AFS control strategy. Based on the results obtained, the CNF control technique improved the transient performances of yaw rate response with minimum overshoot, faster rise time and settling time for a J-turn cornering maneuver and excellent tracking performances in the single lane change maneuver. As a conclusion, the CNF control technique is able to enhance the vehicle lateral dynamic control and vehicle maneuverability. For future works, the CNF control technique will be integrate with robust control technique such as sliding mode control to cater an external disturbances and uncertainties of vehicle parameters
Show more

10 Read more

Mobile Robot Navigation for Person Following in Indoor Environments

Mobile Robot Navigation for Person Following in Indoor Environments

With the mechanism for using navigation functions in practical environments in place, the need to incorporate obstacle motion into the path planning framework for a robotic person follower can be addressed. Navigation functions in their original form [ 61 ] were designed for use in static environments. However, it was shown math- ematically by Chen et al. [ 72 ], and experimentally by Widyotriatmo and Hong [ 74 ] that the stability of this path planner is not affected by its use in dynamic obstacle environments. Hence, in our own previous work [ 78 , 79 ], we used a modification of navigation functions called ‘predictive fields path planning’ to incorporate the motion of obstacles into the navigation function path planner. To do this, each obstacle with an ellipse which is representative of its direction of motion and velocity along that vector. Then, the repulsion felt by the robot from an obstacle was characterized by a function of the actual obstacle position and its predicted path inside its elliptical envelope. This formulation has echoes of the concept of ‘danger’ posed by an ob- stacle’s motion, which has been used in the context of potential fields path planning [ 80 , 81 , 82 , 83 ]. The elliptical field formulation and its simulation results are presented in Sections 2.2.1 and 2.2.4 , respectively.
Show more

178 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Flores in his study tried to identify the students who had a problem to passing the courses at Cordoba University. The Artificial Neural Network model was developed and used to predict the students’ grades [9]. However, Flores obtained his data from MOODLE logs (Modular Object-Oriented Dynamic Learning Environment). He applied his experiment using MOODLE Database that contained 240 students in methodology and programming technology course, and then Flores worked to simplify the experimental work as much as possible by reducing the range of grades to pass or fail.
Show more

9 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

designed workspace composed of 200 trials; each trial contains 12 dynamic obstacles and 12 static obstacles. The positions of these obstacles are initially predefined and stayed permanent in all trials. The dynamic obstacles are moving in straight lines without changing their directions during the execution time of each trial. But, the orientation angle of all dynamic obstacles is either incremented or decremented in each consecutive trial. Moreover, the movement direction of G and the starting positions of R and G are chosen randomly in each trial, where the movement direction of the target is either up, down, right or left. If any trial in an experiment has no facing between the R and an obstacle, it is repeated with another random selection of positions of R and G until a facing takes place. One of these trials is shown in Fig. 9, which represents the GNP-RL control of R in trial number 143 of one of the conducted experiment. It can be seen that R, which moves to the left, exceeds a dynamic obstacle (d10) and two static obstacles (s2 and s1), respectively, before catching the target which is moving down.
Show more

13 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

experts[33].(Mohammad & Al Saiyd, 2010). The expert system is the program that stores the knowledge in a knowledge-base and executes a set of procedures and preconditions to arrive at the final results with the help of the specialists to be able to reach the optimal situation [11]. The expert system stores the knowledge from the expertise and self-knowledge which called Meta knowledge which has already found a place in market position. Normally, expert system consists of the following components: (i) end user interface, (ii) inference engine, and (iii) knowledge base ([4]; [9]; [11] ; [19]). Last decade, however, shows that a growing number of organizations have shifted their informational systems towards a rule-based expert system approach [33]. This fact generates the need for new tools and environments that intelligently port the legacy systems in modern, extensible and scalable knowledge-integrated systems [16]. The power of solving the problems in the expert system is to acquire the knowledge and structure to employ them in expert system services ([15]; [28]). Therefore the achievement of expert system completely depends ongoing on how it fits the element which works as one. 5. PROPOSED EXPERT SYSTEM
Show more

13 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

In addition to designing an efficient approach to study the Haar weighting factor and its impact on image compression and then study the retrieving of original images after the decompres[r]

11 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Malhotra [6] has conducted a study related to mobile Malware and several techniques are used for malware detection. Two main techniques are usually utilized by researchers, signature-based and anomaly-based. In the signature-based techniques, sets instruction patterns are studied and analyzed, while in anomaly-based the unusual activities can be detected. The result has suggested that the signature based techniques can be enhanced using DNA matching techniques applied in other domains.

8 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

2353 movies and achieved 97% accuracy. Twitter was used to monitor the U.S. presidential debate in 2008, Diakopoulos [3]. Some text classification researches for sentiment analysis in Indonesian language have also been conducted. Nur and Santika [6] used tweets as dataset and SVM as classification method, obtained 73.07% accuracy for mobile phone brand. Naradhipa and Purwarianti [5] conducted sentiment classification for product or service companies based on 180 data taken from Facebook, and achieved 86.66% accuracy using SVM method. Tweet classification for traffic jam in Bandung was conducted by Rodiansyah, with SVM method, which achieved 92% accuracy from 100 tweets [9]. Classification process from some related work tends to perform classification limited to a particular tweet entity, as Go [4] and Rao [8] who used emoticon for sentiment classification. Pang used hashtag for sentiment classification and conducted a comparison of several classifier methods [7]. Bifet removes mentions, URLs and emoticons from tweets [2]. Research by Nur [6] and Rodiansyah [9] also reduced tweet entities by removing URLs, mentions, and hashtags from tweets. Technically, tweet has multiple entities, i.e. media, URL, mention, hashtag, emoticon and retweet. Each entity can be used for text classification. For example, to post longer than 140 characters on Twitter called extended tweet, various tools can be used to include a link so people can continue reading the full message.
Show more

7 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Its clearly that from all above simulation results analysis that, some of these physical signal parameters have significant effects on BER such as modulation techniques and the binary or[r]

11 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

2395 global market of mobile technology (Holla and Katti, 2012 in [7]). The number of cellular users in Indonesia is estimated to reach 100 million (Kompas, 2013 in [8]). Mobile applications also allow rapid response to users wherever they are. (Ciuera, 2010 in [9]). In return, this will help bridge the gap between supply of pertinent information on adequacy of animals for sacrifice which eventually help educate and train laymen in this area. Studies on web based expert reliant system has been previously conducted such as: (1) expert reliant system on infants and pregnancy [10]; (2) expert reliant system on general symptoms of common diseases [11]; and (3) expert reliant system on financial planning [12].
Show more

13 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Secure key generation and re-keying without increasing the storage and communication overhead, is really challenging in MANET. The system performs group key reconstructions frequently whenever mobile nodes dynamically join or leave the networks. However, the cost of communication and key management during dynamic join and leave of group members is more.

10 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

The network operators are striving for the optimization of transmission resources while achieving network performance and efficiency. The current optical networking is rolling out towards the next generation intelligent optical network to offer high capacity and better quality according to the attribution of the service. One of core problems in optical network is path computation which involves finding the route between source to destination with appropriate wavelength. The constrained optical path computation involves finding the route with appropriate wavelength while optimizing one or more criteria (ex: less congestion). At present scenario, the centralized PCE with GMPLS control plane could control the optical network with traffic engineering. This approach may be incapable or costlier for the next generation voluminous and dynamic application needs with range of QoS gurantees. The PCE has to rely on a certain routing protocol along with some path cost measures, may not explore the required optimal solutions space, and end up with the best effort path most of the time. Moreover the traffic engineering can potentially add additional cost while maintaining the quality of the path. This article intends a path computation algorithm selection framework amenable for the next generation software defined optical network to solve the problem of QoS constrained path computation. The framework exploits the right proportion of enabling technologies to realize the constrained optical flows in a cost effective and optimal manner. The simulation study was performed to analyze the characteristics of the PCE based algorithm selection model in the SDN based optical network.
Show more

13 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Cross chaotic map is an amalgamation of two chaotic maps, Logistic, and Chebyshev, the equation is being referenced from [9] Both, these algorithms are one dimensional and non-linear dynamic systems and in order to reduce doing the multipart calculations, it is more efficient to combine these chaotic maps as shown in equations 10 and 11 and achieve better security level by using the resultant map in two dimensions. As per the evaluation in [10], for values, of μ=2 and k=6 the system produces great dynamic behaviour. Like Duffing map the points x 0 =0.1933 and y 0 =0.8087
Show more

7 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Computational time in matching process may rely on many factors including the image size, block size, huge number of overlapping blocks, large feature vector dimension, method used in fe[r]

15 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

ABSTRACT This research examines the role of manger experience and formal methodology in software development, such as Reporting to senior management, Communication with users, Planning a[r]

10 Read more

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE 
ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

GENETIC NETWORK PROGRAMMING REINFORCEMENT LEARNING BASED SAFE AND SMOOTH MOBILE ROBOT NAVIGATION IN UNKNOWN DYNAMIC ENVIRONMENTS

Web-Expert system (Web-ES) is used to recognize the symptoms early in women pregnancy disorders. Every pregnancy risk factors will endanger the safety of the mother and the baby, if the information obtained is less in the treatment of pregnancy disorder. This study aims to build web-based expert systems (ES), such as a doctor or a patient to diagnose pregnancy in any place, so it can help women to know about the symptoms of pregnancy disorder. ES is analyzed using forward chaining (FC) method and the Bayesian theorems. One of the Techniques that has been used to make a decision tree, then does a search with FC and the calculation of the probability by Bayesian. Based on the selected input symptoms dataset used 35 patients, the results of a pregnancy disorder which have the highest risk of disruption in eclampsia, with a value of 97% and the suitability of 82.86% system accuracy. Subsequent research, we perform hybrid Bayesian theorem and FC with fuzzy-neural network environments to produce values higher accuracy and will also make a decision in group clinical results.
Show more

11 Read more

Show all 10000 documents...