These equations mathematically model the behaviour of a limb in terms of a knowledge domain-independent, link-segment model, such as idealized solids of revolution or a skeleton with fixed-length limbs and perfect pivot joints. The equations of motion necessary for these computations are based on Newtonian mechanics, specifically the Newton–Euler equations of:įorce equal mass times linear acceleration, and Moment equals mass moment of inertia times angular acceleration. Each moment of force can perform positive work to increase the speed and/or height of the body or perform negative work to decrease the speed and/or height of the body. These moments of force may then be used to compute the amount of mechanical work performed by that moment of force. Similarly, inverse dynamics in biomechanics computes the net turning effect of all the anatomical structures across a joint, in particular the muscles and ligaments, necessary to produce the observed motions of the joint. When combined with passive joint control in a collaborative effort with a control group, Bayo's inverse dynamics approach led to exponentially stable tip-tracking control for flexible multi-link robots. Extending this method to the nonlinear multi-flexible-link case was of particular importance to robotics. This approach yielded non-causal exact solutions due to the right-half plane zeros in the hub-torque-to-tip transfer functions. Until this discovery, they had not been able to work backwards to calculate the movements of the motors required to generate a particular complicated motion., Bayo's work began with the application of frequency-domain methods to the inverse dynamics of single-link flexible robots. This is known as the forward dynamics problem. Researchers can predict the motion of a robot arm if they know how the motors will move. Each motor must be supplied with just the right amount of electric current, at just the right time. In the case of a robot arm, the "muscles" are the electric motors which must turn by a given amount at a given moment. Before the arm moves, the brain calculates the necessary movement of each muscle involved and tells the muscles what to do as the arm swings. Humans can perform very complicated and precise movements, such as controlling the tip of a fishing rod well enough to cast the bait accurately. This solution calculates how each of the numerous electric motors that control a robot arm must move to produce a particular action. The "inverse dynamics problem" in Robotics Engineering was solved by Eduardo Bayo in 1987. Within robotics, inverse dynamics algorithms are used to calculate the torques that a robot's motors must deliver to make the robot's end-point move in the way prescribed by its current task. The fields of robotics and biomechanics constitute the major application areas for inverse dynamics.
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