We have taken the agent architecture sensors, effectors, and processors as given, and we have concentrated on the agent program. The success of real robots depends at least as much on the design of sensors and effectors that are appropriate for the task.
Sensors
Sensors are the perceptual interface between robots and the environment. Passive sensors, such as cameras, are true observers of the environment: they capture signals that are generated by other sources in the environment. Active sensors, such as sonar, send energy into the environment. They rely on the fact that this energy is reflected back to the sensor. Active sensors tend to provide more information than passive sensors, but at the expense of increased power consumption and with a danger of interference when multiple active sensors are used at the same time. Whether active or passive, sensors can be divided into three types, depending on whether they sense the environment, the robot’s location, or the robot’s internal configuration.
Range finders are sensors that measure the distance to nearby objects. In the early 1 days of robotics, robots were commonly equipped with sonar sensors. Sonar sensors emit directional sound waves, which are reflected by objects, with some of the sound making it back into the sensor. The time and intensity of the returning signal indicate the distance to nearby objects. Sonar is the technology of choice for autonomous underwater vehicles. Stereo vision relies on multiple cameras to image the environment from slightly different viewpoints, analyzing the resulting parallax in these images to compute the range of surrounding objects. For mobile ground robots, sonar and stereo vision are now rarely used, because they are not reliably accurate.
Most ground robots are now equipped with optical range finders. Just like sonar sensors optical range sensors emit active signals (light) and measure the time until a reflection of this signal arrives back at the sensor. the time of the flight camera. This camera acquires range images like the one shown in Figure 25.3(b) at up to 60 frames per second Other range sensors use laser beams and special 1-pixel cameras that can be directed using complex arrangements of mirrors or rotating elements. These sensors are called scanning lidars (short for light detection and ranging). Scanning lidars tend to provide longer ranges
than the time of flight cameras and tend to perform better in bright daylight. Other common range sensors include radar, which is often the sensor of choice for a UAVS. Radar sensors can measure distances of multiple kilometers. On the other extreme end of the range, sensing are tactile sensors such as whiskers, bump panels, and touch-sensitive skin. These sensors measure range based on physical contact and can be deployed only for sensing objects very close to the robot
A second important class of sensors is location sensors. Most location sensors use range sensing as a primary component to determine location. Outdoors, the Global Positioning System (GPS) is the most common solution to the localization problem. GPS measures the distance to satellites that emit pulsed signals. At present, there are 31 satellites in orbit. transmitting signals on multiple frequencies. GPS receivers can recover the distance to these satellites by analyzing phase shifts By triangulating signals from multiple satellites, GPS receivers can determine their absolute location on Earth to within a few meters. Differential GPS involves a second ground receiver with a known location, providing millimeter accuracy under ideal conditions. Unfortunately, GPS does not work indoors or underwater, Indoors, localization is often achieved by attaching beacons in the environment at known locations. Many indoor environments are full of wireless base stations, which can help robots localize through the analysis of the wireless signal. Underwater, active sonar beacons can provide a sense of location, using sound to inform AUVS of their relative distances to those beacons.
The third important class is proprioceptive sensors, which inform the robot of its own motion. To measure the exact configuration of a robotic joint, motors are often equipped with shaft decoders that count the revolution of motors in small increments. On robot arms, shaft decoders can provide accurate information over any period of time. On mobile robots, shaft decoders that report wheel revolutions can be used for odometry-the measurement of distance traveled. Unfortunately, wheels tend to drift and slip, so odometry is accurate only over short distances. External forces, such as the current for AUVs and the wind for UAVS, increase positional uncertainty. Inertial sensors, such as gyroscopes, rely on the resistance of mass to the change of velocity. They can help reduce uncertainty.
Other important aspects of the robot state are measured by force sensors and torque sensors. These are indispensable when robots handle fragile objects or objects whose exact shape and location are unknown. Imagine a one-ton robotic manipulator screwing in a light bulb. It would be all too easy to apply too much force and break the bulb. Force sensors allow the robot to sense how hard it is gripping the bulb, and torque sensors allow it to sense how hard it is turning. Good sensors can measure forces in all three translational and three rotational directions. They do this at a frequency of several hundred times a second so that a robot can quickly detect unexpected forces and correct its actions before it breaks a light bulb.
Effectors
Effectors are the means by which robots move and change the shape of their bodies. To understand the design of effectors, it will help to talk about motion and shape in the abstract, using the concept of a degree of freedom (DOF) We count one degree of freedom for each independent direction in which a robot, or one of its effectors, can move. For example, a rigid mobile robot such as an AUV has six degrees of freedom, three for its (r, y, z) location in space and three for its angular orientation, known as yaw, roll, and pitch. These six degrees define the kinematic state or pose of the robot. The dynamic state of a robot includes these six plus an additional six dimensions for the rate of change of each kinematic dimension, that is, their velocities.
For nonrigid bodies, there are additional degrees of freedom within the robot itself. For example, the elbow of a human arm possesses two degrees of freedom. It can flex the upper arm towards or away, and can rotate right or left. The wrist has three degrees of freedom. It can move up and down, side to side, and can also rotate. Robot joints also have one, two, or three degrees of freedom each. Six degrees of freedom are required to place an object, such as a hand, at a particular point in a particular orientation. The arm in Figure 25.4(a) has exactly six degrees of freedom, created by five revolute joints that generate rotational motion and one prismatic joint that generates sliding motion. You can verify that the human arm as a whole has more than six degrees of freedom by a simple experiment: put your hand on the table and notice that you still have the freedom to rotate your elbow without changing the configuration of your hand. Manipulators that have extra degrees of freedom are easier to For mobile robots, the DOFs are not necessarily the same as the number of actuated elements. Consider, for example, your average car: it can move forward or backward, and it can turn, giving it two DOFs. In contrast, a car’s kinematic configuration is three-dimensional: on an open flat surface, one can easily maneuver a car to any (x,y) point, in any orientation. Thus, the car has three effective degrees of freedom but two controllable degrees of freedom. We say a robot is nonholonomic if it has more effective DOFs than controllable DOFs and holonomic if the two numbers are the same. Holonomic robots are easier to control it would be much easier to park a car that could move sideways as well as forward and backward-but holonomic robots are also mechanically more complex. Most robot arms are holonomic, and most mobile robots are nonholonomic.
Mobile robots have a range of mechanisms for locomotion, including wheels, tracks, VE, and legs. Differential drive robots possess two independently actuated wheels (or tracks), one on each side, as on a military tank. If both wheels move at the velocity, the robot moves in a straight line. If they move in opposite directions, the robot turns on the spot. An alternative is the synchro drive, in which each wheel can move and turn around its own axis. To avoid chaos, the wheels are tightly coordinated. When moving straight, for example, all wheels point in the same direction and move at the same speed. Both differential and synchro drives are nonholonomic. Some more expensive robots use holonomic drives, which have three or more wheels that can be oriented and moved independently.
Some mobile robots possess arms. displays a two-armed robot. This robot’s arms use springs to compensate for gravity, and they provide minimal resistance to external forces. Such a design minimizes the physical danger to people who might stumble into such a robot. This is a key consideration in deploying robots in domestic environments. Legs, unlike wheels, can handle rough terrain. However, legs are notoriously slow on flat surfaces, and they are mechanically difficult to build. Robotics researchers have tried designs ranging from one leg up to dozens of legs. Legged robots have been made to walk, run, and even hop-as we see with the legged robot. This robot is dynamically stable, meaning that it can remain upright while hopping around. A robot that can remain upright without moving its legs is called statically stable. A robot is statically stable if its center of gravity is above the polygon spanned by its legs. The quadruped (four-legged) robot may appear statically stable. However, it walks by lifting multiple legs at the same time, which renders it dynamically stable. The robot can walk on snow and ice, and it will not fall over even if you kick it (as demonstrated in videos available online). Two-legged robots such as those are dynamically stable.
Other methods of movement are possible: air vehicles use propellers or turbines; underwater vehicles use propellers or thrusters, similar to those used on submarines. Robotic blimps rely on thermal effects to keep themselves aloft.
Sensors and effectors alone do not make a robot. A complete robot also needs a source of power to drive its effectors. The electric motor is the most popular mechanism for both manipulator actuation and locomotion, but pneumatic actuation using compressed gas and hydraulic actuation using pressurized fluids also have their application niches.
