Object tracking has become one of the important research areas in robotics. In this paper, we propose a vision based color object tracking by Khepera II mobile robot. The object tracking is realized by color segmentation through image threshold. The wireless camera mounted on the robot will capture the image in front of its viewing range and based on the color property of the target object, the...

An experimental comparison among the main behavioral control techniques for autonomous mobile robots is presented in this paper. The behavioral algorithms tackle the problem in a similar way: they decompose the mission planning of the robot in simple tasks; each task is then approached independently from the others and, at the end, the behavioral algorithms arrange the tasks’ output to give an ...

This paper provides a new approach to the multi-robot path planning problem predicting the position of a dynamic obstacle which undergoes linear motion in the given workspace changing its direction at regular intervals of time. The prediction is done in order to avoid collision of the robots with the dynamic obstacle. First the work is done in simulation environment then the entire work has bee...

The Autonomous Robotics and Control Systems Laboratory at the University of Washington has developed a testbed consisting of seven K-Team Khepera II miniature robots, a global vision system and a custom-designed infrared communication structure. The purpose of the testbed is to provide a platform for the real-world testing of distributed and centralized control algorithms for groups of autonomo...

We have developed a neuro-robot-hybrid system using a living neuronal network and a miniature moving robot. The living network of rat hippocampal neurons can distinguish patterns of action potentials evoked by different inputs, suggesting that a cultured neuronal network can represent particular states as symbols. We used a Khepera II robot and a robot made using a LEGO mindstorm NXT kit to int...

An incremental approach is used to simulate the evolution of neural controllers for robust obstacle-avoidance in a Khepera robot and proves to be more eecient than a direct approach. During a rst evolutionary stage, obstacle-avoidance controllers in medium-light conditions are generated. During a second evolutionary stage, controllers avoiding strongly-lighted regions, where the previously acqu...

The Khepera system is a toolkit for the rapid implementation and long-term maintenance of domain speci c languages (DSLs). Our viewpoint is that DSLs are most easily implemented via source-tosource translation from the DSL into another language and that this translation should be based on simple parsing, sophisticated tree-based analysis and manipulation, and source generation using prettyprint...

The Khepera system is a toolkit for the rapid implementation and long-term maintenance of domain speciic languages (DSLs). Our viewpoint is that DSLs are most easily implemented via source-to-source translation from the DSL into another language and that this translation should be based on simple parsing, sophisticated tree-based analysis and manipulation, and source generation using pretty-pri...

The Khepera system is a toolkit for the rapid implementation and long-term maintenance of domain speci c languages (DSLs). Our viewpoint is that DSLs are most easily implemented via source-tosource translation from the DSL into another language and that this translation should be based on simple parsing, sophisticated tree-based analysis and manipulation, and source generation using prettyprint...