Legged robot

Legged robots are a type of mobile robot, which use articulated limbs, such as leg mechanisms, to provide locomotion. They are more versatile than wheeled robots and can traverse many different terrains, though these advantages require increased complexity and power consumption. Legged robots often imitate legged animals, such as humans or insects, in an example of biomimicry. Legged robots are a type of mobile robot, which use articulated limbs, such as leg mechanisms, to provide locomotion. They are more versatile than wheeled robots and can traverse many different terrains, though these advantages require increased complexity and power consumption. Legged robots often imitate legged animals, such as humans or insects, in an example of biomimicry. Legged robots, or walking machines, are designed for locomotion on rough terrain and require control of leg actuators to maintain balance, sensors to determine foot placement and planning algorithms to determine the direction and speed of movement. The periodic contact of the legs of the robot with the ground is called the gait of the walker. In order to maintain locomotion the center of gravity of the walker must be supported either statically or dynamically. Static support is provided by ensuring the center of gravity is within the support pattern formed by legs in contact with the ground. Dynamic support is provided by keeping the trajectory of the center of gravity located so that it can be repositioned by forces from one or more of its legs. Legged robots can be categorized by the number of limbs they use, which determines gaits available. Many-legged robots tend to be more stable, while fewer legs lends itself to greater maneuverability. One-legged, or pogo stick robots use a hopping motion for navigation. In the 1980s, Carnegie Mellon University developed a one-legged robot to study balance. Berkeley's SALTO is another example. Bipedal or two-legged robots exhibit bipedal motion. As such, they face two primary problems: Stability control is particularly difficult for bipedal systems, which must maintain balance in the forward-backward direction even at rest. Some robots, especially toys, solve this problem with large feet, which provide greater stability while reducing mobility. Alternatively, more advanced systems use sensors such as accelerometers or gyroscopes to provide dynamic feedback in a fashion that approximates a human being's balance. Such sensors are also employed for motion control and walking. The complexity of these tasks lends itself to machine learning. Simple bipedal motion can be approximated by a rolling polygon where the length of each side matches that of a single step. As the step length grows shorter, the number of sides increases and the motion approaches that of a circle. This connects bipedal motion to wheeled motion as a limit of stride length.