this article presents an implementation of a reinforcement learning (rl) method for a snake like robot navigation. the paper starts with developing kinematics and dynamics model of a snake robot in serpentine locomotion followed by performing simulation and finishes with actual experimentation. first, gibbs-appell's method is used to obtain the robot dynamics. the robot is also modeled in simme...

mobile robot navigation is one of the basic problems in robotics. in this paper, a new approachis proposed for autonomous mobile robot navigation in an unknown environment. the proposedapproach is based on learning virtual parallel paths that propel the mobile robot toward the trackusing a multi-layer, feed-forward neural network. for training, a human operator navigates themobile robot in some...

In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...

A simple easy to implement algorithm is proposed to address wall tracking task of an autonomous robot. The robot should navigate in unknown environments, find the nearest wall, and track it solely based on locally sensed data. The proposed method benefits from coupling fuzzy logic and Q-learning to meet requirements of autonomous navigations. Fuzzy if-then rules provide a reliable decision maki...

Mobile robot navigation is one of the basic problems in robotics. In this paper, a new approach is proposed for autonomous mobile robot navigation in an unknown environment. The proposed approach is based on learning virtual parallel paths that propel the mobile robot toward the track using a multi-layer, feed-forward neural network. For training, a human operator navigates the mobile robot in ...

This case study investigates the effects of Robot Assisted Language Learning (RALL) on English vocabulary learning and retention of Iranian children with high-functioning autism. Two groups of three male students (6-10 years old) with high-functioning autism participated in the current study. The humanoid robot NAO was used as a teacher assistant to teach English to the RALL group. Both RALL an...

The recent success of machine learning has lead to advancements in robot intelligence and human-robot interaction. It is reported that robots can well understand visual scene information and describe the scenes in language using computer vision and natural language processing methods. Image Question-Answering (QA) systems can be used for human-robot interaction. However, to achieve human-level ...

In many applications the performance of learned robot controllers drags behind those of the respective hand-coded ones. In our view, this situation is caused not mainly by deficiencies of the learning algorithms but rather by an insufficient embedding of learning in robot control programs. This paper presents a case study in which ROLL, a robot control language that allows for explicit represen...