This paper presents a novel, decentralized, control-theoretic approach to address collision avoidance for multi-robot systems. We create a virtual obstacle at the mean position of the robots. A control is be designed such that each robot will avoid the closest obstacle when a collision is possible. The closest obstacle can be the virtual obstacle or the nearest robot. We present two such control laws. The first assumes perfect knowledge of the velocities of all nearby robots and can allow a saturated velocity input for each robot. In practice, the velocities of the other robots are hard to measure or estimate precisely. Therefore, the second control law removes the assumption of known velocities based on a high-gain, robust control scheme. We prove the first control scheme is globally asymptotically stable, and the robust control law is globally uniformly ultimately bounded. To verify the effectiveness of the proposed approach, Monte Carlo simulations and experiments have been conducted.

Various robot platforms have been designed and developed to perform given tasks in a hazardous environment for surveillance, reconnaissance, search and rescue, etc. We considered a terrain-adaptive and transformable hybrid robot platform that is equipped for rapid navigation on flat floors and good performance in overcoming stairs or obstacles. The mode transition is determined and implemented by adaptive driving mode control of the mobile robot. The terrain-adaptive and user-friendly remote control was verified through its navigation performance experiments in real and test-bed environments.

Robot technology is emerging for applications in disaster prevention with devices such as fire-fighting robots, rescue robots, and surveillance robots. In this paper, we suggest an portable fire evacuation guide robot system that can be thrown into a fire site to gather environmental information, search displaced people, and evacuate them from the fire site. This spool-like small and light mobile robot can be easily carried and remotely controlled by means of a laptop-sized tele-operator. It contains the following functional units: a camera to capture the fire site; sensors to gather temperature data, CO gas, and O2concentrations; and a microphone with speaker for emergency voice communications between firefighter and victims. The robot's design gives its high-temperature protection, excellent waterproofing, and high impact resistance. Laboratory tests were performed for evaluating the performance of the proposed evacuation guide robot system.

Fuzzy algorithms provide intuitive method for robot obstacle avoidance. Fuzzy controllers incorporating a design based on lookup tables (LUT) enable faster obstacle avoidance in environment with multiple obstacles. In an earlier study, we introduced a full LUT-based architecture for an 18-rule positive/negative (P/N) fuzzy controller. In this study, the number of fuzzy rules is expanded to 50. Because of the extra rules, the controller apparently needs more LUT(s) buffers. In other words, the buffer size increases with the complexity of the fuzzy controller. Therefore, we propose a LUT sharing method to reduce the buffer size without significantly degrading the performance of the controller. The final objective of this work is to design a LUT-based fuzzy controller whose buffer size is independent of the complexity of the fuzzy system. The proposed method is evaluated by simulating a 50-rule P/N fuzzy controller using Microsoft Robotics Developer Studio (MSRDS). The simulation results show that in comparison with the method not using LUT(s), full LUT-based method and the LUT sharing method reduce the operational time by nearly 80% and 70%, respectively. Although the LUT sharing method needs 1.5 times more operational time than the full LUT methods, it reduces the buffer size by more than 90%.