We present the recent development work on the electrical and hardware design of our modular and scalable mobile robot platform for education and research. The goal of the project is to develop a low-cost and extensible modular mobile robot platform for education and research activities. We present a differential drive robot with distributed input/output modules. The project is scalable to be easily extended to make complex autonomous robot systems including four wheel drive and omnidirectional robots. The software design is based on ROS framework that is based on open source software.
Recently, legged robots have been developed to work in a dangerous space for an investigation, rescue, and so on. This paper introduces a method for a Limb-type robot to move in frame structures such as a ladder or jungle-gym. The proposed method is based on path planning and motion generation. For path planning problem, A* algorithm plans a path while taking the workspace of limbs of the robot in consideration. The robot can then move along the resultant path, and the robot need to stop to hold new supported position on the way. The velocity change for stoppages is decided by mechanical constrains of the robot. The motion is generated from the velocity by Inverse kinematics. After the method is explained, kinematic simulation is conducted, and some problems and the improvement plans are indicated.
An inter-robot learning strategy to track the dynamic changes in the environment is proposed. The robots 'teach' other robots about the changes encountered at remote locations of the map enabling them to achieve efficiency in path planning and task coordination. With the proposed method, a robot is able to learn about the obstacles in remote locations of the map and plans its path by considering the updated obstacle information. This is better than the traditional path planning in which robot has to re-plan its path upon finding obstacles.