Robots that perform autonomous maneuvering in a disaster environment usually dont have perfect understanding of the environment in advance. The robot is continuously evaluating the environment as it proceeds, deciding the optimal way to traverse the environment to get to the goal. A critical aspect of this decision is the robot estimate of the terrain accessibility index, which quantifies how easy it is to navigate through the immediate terrain. This paper represents a new method to calculate terrain accessibility index based on obstacle distance to the robots position. In addition, a Fuzzy Inference System Vector Field Histogram (FISVFH) method has been designed for automating the selection of the robots linear and angular velocities in the VFH (Vector Field Histogram) algorithm, based on the calculated sector accessibility index. The proposed method is a two-input and two-output Fuzzy Inference System, where the current robot heading, and sector accessibility index serve as the input, and the corresponding linear and angular velocities to the VFH algorithm are outputs. The VFH, VFH + and FISVFH are tested both in simulation and experimentation in 4 environments that are known to result in failures in VFH and VFH +, for comparison purposes. In addition, the algorithm was verified through experimental setup of a disaster prone environment. In both simulation and experimentation the results show that FISVFH outperforms VFH and VFH +. It is also shown that the FISVFH algorithm is capable of handling the disaster prone environment. Overall, the FISVFH algorithm enables the robot to get to the goal faster and also produces a smoother path while doing so.

In an effort for human colonization and exploration of the lunar surface there should be a way to store energy for when demand requires it. For energy storage a flywheel can provide a reliable, efficient and low-maintenance system for this need. This paper contains the description of a low-speed flywheel that includes an external rotor and hubless electrical machine. This allows for a high energy low loss machine. For the machine to be hubless it requires the use of active magnetic bearings. In this paper the system model and control algorithm for the active magnetic bearings for the flywheel energy storage system is presented. The simulation and validation of the model is shown.

To support human colonization and exploration of the lunar surface, the generation and storage for the electrical load demands for a lunar day need to be developed. For the operation of storage a Flywheel Energy Storage System could provide a reliable, efficient and low-maintenance method to help provide continuous electrical energy. The Flywheel Energy Storage System described is a low-speed flywheel that includes an external rotor and hubless electrical machine. Understanding the dynamics of the hubless machine is very important for control and described in this paper is the rotational dynamic modeling of the rotor of a low-speed Flywheel Energy Storage System.