The work presented in this thesis focuses on the design and testing of a casualty extraction robot intended to stabilize the head and neck of an unresponsive person. The employment of robots in dangerous locales such as combat zones or the site of a natural disaster has the potential to help keep first responders out of harm's way as well as to improve the efficiency of search and rescue teams. After a review of robotic search and rescue platforms the Semi-Autonomous Victim Extraction Robot(SAVER) is introduced. The necessity of a device intended to support the head and cervical spine during transport on a rescue robot is then discussed. The kinematic and dynamic analyses of various candidate differential mechanisms intended for the head stabilization device are described, and the chosen mechanism is demonstrated in a proof-of-concept device. Following testing with a simple PID controller, it was determined an advanced feedback controller with disturbance rejection capabilities was required. Linear Active Disturbance Rejection Control (LADRC) was chosen for its effectiveness in rejecting perturbations and handling modeling uncertainties. The performance the proposed LADRC control scheme was compared with PID in simulation and the results are presented. Finally, a prototype of the device was designed and built to validate the functionality of the subsystem, and the results of the corresponding experimentation are discussed. / M. S. / Robots can help to keep first responders and medics out of dangerous situations by performing the rescue operation themselves or by collaborating with the field medic to make the process quicker and more efficient. The work presented in this thesis begins with a review of state-of-the-art rescue robots followed by the a brief description of the design of a Semi-Autonomous Victim Extraction Robot (SAVER) intended to rescue injured and incapacitated people. After the SAVER system is briefly described, the necessity of a device intended to support the head and cervical spine during transport is discussed. The head stabilization subsystem could also be implemented as a standalone device for use by paramedics to help free up valuable time that would otherwise be spent in manually stabilizing the head and neck of the injured person

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing cooperation and task sharing between a human operator and a robot with respect to tasks such as navigation, exploration and victim identification. Herein, a unique hierarchical reinforcement learning (HRL) -based semi-autonomous control architecture is presented for rescue robots operating in unknown and cluttered urban search and rescue (USAR) environments. The aim of the controller is to allow a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A new direction-based exploration technique and a rubble pile categorization technique are integrated into the control architecture for exploration of unknown rubble filled environments. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed control architecture.

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing cooperation and task sharing between a human operator and a robot with respect to tasks such as navigation, exploration and victim identification. Herein, a unique hierarchical reinforcement learning (HRL) -based semi-autonomous control architecture is presented for rescue robots operating in unknown and cluttered urban search and rescue (USAR) environments. The aim of the controller is to allow a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A new direction-based exploration technique and a rubble pile categorization technique are integrated into the control architecture for exploration of unknown rubble filled environments. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed control architecture.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21209号 / 情博第662号 / 新制||情||114(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 河原 達也, 教授 鹿島 久嗣, 教授 田中 利幸, 講師 吉井 和佳 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Advances in mobile robot technology allow an increasing variety of applications to be imagined, including: search and rescue, exploration of unknown areas and working with hazardous materials. State of the art robots are able to behave autonomously and without direct human control, using on-board devices to perceive, navigate and reason about the world. Unmanned Aerial Vehicles (UAVs) are particularly well suited to performing advanced sensing tasks by moving rapidly through the environment irrespective of the terrain. Deploying groups of mobile robots offers advantages, such as robustness to individual failures and a reduction in task completion time. However, to operate efficiently these teams require specific approaches to enable the individual agents to cooperate. This thesis proposes coordinated approaches to search scenarios for teams of UAVs. The primary application considered is Wilderness Search and Rescue (WiSaR), although the techniques developed are applicable elsewhere. A novel frontier-based search approach is developed for rotor-craft UAVs, taking advantage of available terrain information to minimise altitude changes during flight. This is accompanied by a lightweight coordination mechanism to enable cooperative behaviour with minimal additional overhead. The concept of a team rendezvous is introduced, at which all team members attend to exchange data. This also provides an ideal opportunity to create a comprehensive team solution to relay newly gathered data to a base station. Furthermore, the delay between sensing and the acquired data becoming available to mission commanders is analysed and a technique proposed for adapting the team to meet a latency requirement. These approaches are evaluated and characterised experimentally through simulation. Coordinated frontier search is shown to outperform greedy walk methods, reducing redundant sensing coverage using only a minimal coordination protocol. Combining the search, rendezvous and relay techniques provides a holistic approach to the deployment of UAV teams, meeting mission objectives without extensive pre-configuration.

Successful development of mechatronic systems requires a combination of targeted hardware and software design. The compact rescue robot (CRR), a quadruped pneumatically-actuated walking robot that seeks to use the benefits garnered from pneumatic power, is a prime example of such a system. This thesis discusses the development and testing of a simulation that will aid in further design and development of the CRR by enabling users to examine the impacts of pneumatic actuation on a walking robot. However, development of an entirely new dynamic simulation specific to the system is not practical. Instead, the simulation combines a MATLAB/Simulink actuator simulation with a readily available C++ dynamics library. This multi-platform approach results in additional incurred challenges due to the transfer of data between the platforms. As a result, the system developed here is designed in the fashion that provides the best balance of realistic behavior, model integrity, and practicality. An analytically derived actuator model is developed using classical fluid circuit modeling together with nonlinear area and pressure curves to model the valve and a Stribeck-Tanh model to characterize the effects of friction on the cylinder. The valve model is designed in Simulink and validated on a single degree-of-freedom test rig. This actuator model is then interfaced with SrLib, a dynamics library that computes dynamics of the robot and interactions with the environment, and validated through comparisons with a CRR prototype. Conclusions are focused on the final composition of the simulation, its performance and limitations, and the benefits it offers to the system as a whole.