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I wish to take this opportunity to express my appreciation to Dr. Feitian Zhang for joining with me as Co‐Author in developing this second edition of Mobile Roots. He has demonstrated a high level of knowledge and skill in the area of autonomous underwater robots (AUVs) and adds a new dimension to the book with this contribution. It has been a pleasure working together on this project.

Mobile robots, as the name implies, have the ability to move around. They may travel on the ground, on the surface of bodies of water, under water, and in the air. This is in contrast with fixed‐base robotic manipulators that are more commonplace in manufacturing operations such as automobile assembly, aircraft assembly, electronic parts assembly, welding, spray painting, and others. Fixed‐base robotic manipulators are typically programmed to perform repetitive tasks with perhaps limited use of sensors, whereas mobile robots are typically less structured in their operation and likely to use more sensors.

As a mobile robot performs its tasks, it is important for its supervisor to maintain knowledge of its location and orientation. Only then can the sensed information be accurately reported and fully exploited. Thus navigation is essential. Navigation is also required in the process of directing the mobile robot to a specified destination. Along with navigation is the need for stable and efficient control strategies. The navigation and control operations must work together hand‐in‐hand. Once the mobile robot has reached its destination, the sensors can acquire the needed data and either store it for future transfer or report it immediately to the next level up. Thus, there is a whole system of functions required for effective use of mobile robots.

Mobile robots may be operated in a variety of different modes. One of these is the teleoperated mode in which a supervisor provides some of the instructions. Here sensors including cameras provide information from the robot to the supervisor that enables him or her to assess the situation and decide on the next course of action. The supervision may be very complete, leaving no decision making to the robot, or it may be at a high level only, leaving details to be worked out by algorithms residing on the robot. Some examples of this type of operation are the Mars rovers and the walking robots that descended down into the volcano on Mount Saint Helens in the state of Washington. Additional applications include the handling of hazardous materials such as nuclear waste or explosives and the search in war operations for explosives such as landmines. Other examples are unmanned air vehicles (UAVs) and AUVs that can be used for reconnaissance operations. The trajectory may be prespecified with the provision for intervention and redirection as the circumstances dictate.

One of the more interesting stories involving a teleoperated mobile robot took place in Prince William County, Virginia in the nineties. The police had a suspect cornered in an apartment house and decided that since he was armed they would send in their mobile robot. It was a tracked vehicle with a camera, an articulated manipulator, and a stun gun. Under the direction of a supervisor the robot was able to climb the stairs, open the apartment door, open a closet door, lift a pile of clothes off the suspect, and then stun him so that he could be apprehended. This served a very useful purpose and alleviated the need for the police officers to subject themselves to risk of injury or death.

Another possible mode is autonomous operation. Here the robot operates without external inputs except those inputs obtained through its sensors. Often there is a random element to the motion with sensors for collision avoidance and/or signal seeking. One example of this type of operation was the miniature solar‐powered lawn mowers at the CIA in Langley, Virginia. These mobile robots were the size of a dinner plate and had razor sharp blades. The courtyard in which they worked was quite smooth with well‐defined boundaries. Each robot could move in a random direction until hitting an obstacle at which time it switched to a new direction. Another example of this autonomous robotic behavior is a swimming‐pool cleaner. This device moves about the pool sucking up any debris on the bottom of the pool and causing it to be pumped into the filtration system. The motion of the mobile robot seems to be somewhat random with the walls of the pool providing a natural boundary. Similar devices exist for vacuuming homes or offices.

A very exciting and recent example of an underwater semi‐autonomous vehicle was the crossing of the Atlantic Ocean, from the coast of New Jersey to the coast of Spain, by the deep‐sea glider Scarlet. This 8‐ft long, 135 lb, unmanned vehicle was the product of a research team at Rutgers University and Teledyne Webb Research. The voyage took 221 days, extended over 4,600 miles, and provided data on the water temperature and salinity as a function of depth. The glider was powered by a battery that alternately pumped water out of the front portion of the vehicle to cause it to rise and took on water to cause it to dive. The battery could also be shifted forward or backward to modify the weight distribution and thereby adjust the glide angle. As the glider dove or climbed, its hydrodynamic wings gave it forward motion in much the same manner as that of a toy airplane glider dropped from a second floor window. It was equipped with a rudder for steering. Normally it traveled down to a depth of 600 ft below the surface of the ocean and then up to within 60 ft of the surface. A few times per day it would surface to get a GPS fix on its position, make radio contact with its supervisor and obtain a new way‐point to head toward. Apparently the vehicle was equipped with an inertial measurement device that would provide heading information while underwater. (Washington Post, Tuesday, December 15, 2009, health and science Section pages E1 and E6.) As was mentioned, an important application of AUVs such as this is data collection of variables such as water temperature and salinity as a function of location, including depth.

Examples of mobile robots in manufacturing facilities include wheeled vehicles used for material transfer from one work station to another. Here a line painted on the floor may designate the path for the mobile robot to follow. Optical sensors sense the boundaries of the line and give commands to the steering system to cause the mobile robot to follow along the track. Schemes such as this can also be used for mobile robots whose assignment is to perform inventory checks or security checks in a large facility such as a warehouse. Here the path for the mobile robot is specified and the sensors acquire and store the required information as the robot makes its rounds.

There are two basic types of steering used by mobile robots operating on the ground. For both of these types of steering, the mobile robot may have one or two front wheels. One type is front‐wheel steering much like that of an automobile. This type of steering presents interesting challenges to the controller, because it yields a nonzero turning radius. This radius is limited by the length of the robot and the maximum steering angle.

The other type of steering involves independent wheel control for each side. By rotating the left and right wheels in opposite directions at the same speed, the robot can be made to turn while in place, i.e., at a zero turning radius. Tracked vehicles use this same type of differential‐drive steering strategy, there often referred to as skid steering.

Examples of mobile robots also include, as we mentioned earlier, AUVs such as underwater gliders, whose diverse applications range from oil/gas exploration and environmental monitoring to search and rescue and national harbor security. Due to the complex interaction between surrounding fluid and AUVs, hydrodynamics play an important role in determining vehicle dynamics which exhibits high nonlinearity. In addition, AUVs operate in open water environments typically in a truly three‐dimensional trajectory. Therefore, it is essential to establish the dynamic model of AUVs and further investigate how to control AUV’s dynamic motions given the unique propulsion and steering mechanisms such as buoyancy adjustment and control surfaces (e.g., a rudder or an elevator).

The objectives of this book are to serve as a textbook for a one‐semester graduate course on wheeled surface robots as well as AUVs and also to provide a useful reference for one interested in these fields. The book presumes knowledge of modern control and random processes. Exercises are included with each chapter. Prior facility with digital simulation of dynamic systems is very helpful but may be developed as one takes the course. The material lends itself well to the inclusion of a course project if one desires to do so.