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We describe techniques for interactively controlling bipedal articulated figures through kinematic constraints. These constraints model certain behavioral tendencies which capture some of the characteristics of human-like movement, and give us control over such elements as the figures ’ balance

this paper. When a GP run has finished, the final output of the GP subsystem is a single controller program. This controller program is the one which, when used to govern the actions of a simulated agent, resulted in the best rated agent according to the user-supplied fitness metric. This controller program may then be used to generate the motion control needed for the animation.

For creating real-time animations of 3D characters we introduce motion models, which model a certain kind of motion like walk or wave. Each motion model has its own set of parameters controlling the specific characteristics of a motion. These parameters can be changed while a motion model is executed, thus this allows a change of the characteristics of a motion in real-time. The motion models produce animations by applying operators on short clips of animation and blending the results together. The parameters of the motion model determine the operators and the animation clips which are used to create the appropriate animation.

We present a physics-based system for the guided animation of articulated figures. Based on an efficient forward dynamics simulator, we introduce a robust feedback control scheme and a fast two-stage collision response algorithm. A user of our system provides kinematic trajectories for those

In this paper we extend previous work on automatic motion synthesis for physically realistic 2D articulated figures in three ways. First, we describe an improved motion-synthesis algorithm that runs substantially faster than previously reported algorithms. Second, we present two new techniques

We describe techniques for interactively controlling bipedal articulated figures through kinematic constraints. These constraints model certain behavioral tendencies which capture some of the characteristics of humanlike movement, and give us control over such elements as the figures ' balance

An articulated figure is often modeled as a set of rigid segments connected with joints. Its configuration can be altered by varying the joint angles. Although it is straightforward to compute figure configurations given joint angles (forward kinematics), it is not so to find the joint angles

Abstract. In this paper we explore the use of Petri Nets as a tool to control the movements of articulated figures in computer animations. This approach permits us to describe the animation sequence by means of the treatment of events present in its execution. An advantage of this method

In this paper, we present an interactive system to transfer and concatenate motions in different articulated figures, such as human and dog. This system first constructs a union skeleton that contains both bone structures with bone correspondence manually assigned by users, then aligns the initial