This paper describes the application of space time constraints to creating transitions between segments of human body motion. The motion transition generation uses a combination of spacetime constraints and inverse kinematic constraints to generate seamless and dynamically plausible transitions between motion segments. We use a fast recursive dynamics formulation which makes it possible to use spacetime constraints on systems with many degrees of freedom, such as human figures. The system uses an interpreter of a motion expression language to allow the user to manipulate motion data, break it into pieces, and reassemble it into new, more complex, motions. We have successfully used the system to create basis motions, cyclic data, and seamless motion transitions on a human body model with 44 degrees of freedom. Additional Keywords and Phrases: computer animation, inverse kinematics, motion capture, motion control, human figure animation, cyclification. CR Categories and SubjectDescriptions: I.3.7 [Computer Graphics]:

This paper reviews some of the accomplishments in the field of robot dynamics research, from the development of the recursive Newton-Euler algorithm to the present day. Equations and algorithms are given for the most important dynamics computations, expressed in a common notation to facilitate their presentation and comparison. 1

Figure 1: Adaptive dynamics of articulated characters. In this complex scene, 200 human characters, represented by 17,800 rigid bodies and 19,000 degrees of freedom, are suddenly pushed away from the camera due to applied forces. Our adaptive dynamics algorithm allows an animator to progressively reduce the number of simulated joints in the characters as their distance to the camera increases, while automatically determining which joints should be animated to best approximate the characters motion. Depending on the total amount of simplification specified by the animator, a potentially significant speed-up can be achieved over typical linear-time forward dynamics algorithms. Abstract: Forward dynamics is central to physically-based simulation and control of articulated bodies. We present an adaptive algorithm for computing forward dynamics of articulated bodies: using novel motion error metrics, our algorithm can automatically simplify the dynamics of a multi-body system, based on the desired number of degrees of freedom and the location of external forces and active joint forces. We demonstrate this method in plausible animation of articulated bodies, including a large-scale simulation of 200 animated humanoids and multi-body dynamics systems with many degrees of freedom. The graceful simplification allows us to achieve up to two orders of magnitude performance improvement in several complex benchmarks.

This article describes a theory of the computations underlying the selection of coordinated motion patterns, especially in reaching tasks. The central idea is that when a spatial target is selected as an object to be reached, stored postures are evaluated for the contributions they can make to the task. Weights are assigned to the stored postures, and a single target posture is found by taking a weighted sum of the stored postures. Movement is achieved by reducing the distance between the starting angle and target angle of each joint. The model explains compensation for reduced joint mobility, tool use, practice effects, performance errors, and aspects of movement kinematics. Extensions of the model can account for anticipation and coarticulation effects, movement through via points, and hierarchical control of series of movements. The goal of this research is a unified theory of the planning and control of physical action. Such a theory, as several authors have noted (Jeannerod, in press; Rosenbaum, 1991; Wing, 1993), has been lacking. Instead, specialized models have been designed to account for data from different tasks. The sentiment

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Most robot controllers today employ a single processor architecture. As robot control requirements become more complex, these serial controllers have difficulty providing the desired response time. Additionally, with robots being used in environments that are hazardous or inaccessible to humans, fault-tolerant robotic systems are particularly desirable. A uniprocessor control architecture cannot offer tolerance of processor faults. Use of multiple processors for robot control offers two advantages over single processor systems. Parallel control provides a faster response, which in turn allows a finer granularity of control. Processor fault tolerance is also made possible by the existence of multiple processors. There is a trade-off between performance and the level of fault tolerance provided. This paper describes a shared memory multiprocessor robot controller that is capable of providing high performance and processor fault tolerance. We evaluate the performance of this controller, a...

Specifying the motion of an animated linked figure such that it achieves given tasks (e.g., throwing a ball into a basket) and performing the tasks in a realistic fashion (e.g., gracefully, and following physical laws such as gravity) has been an elusive goal for computer animators. The spacetime constraints paradigm has been shown to be a valuable approach to this problem, but it suffers from the computational complexity growth as creatures and tasks approach those one would like to animate. There are two sources which contribute to the complexity problem: one is the symbolic processing of the animator's constraints and the objective functions derived from the physical models and the second lies in the numerical optimization phase. This thesis reports on work to enhance the spacetime constraints techniques both symbolically and numerically to significantly speed up computations. Our first contribution is to develop a new symbolic interface with a recursive evaluation scheme so that th...

In this work an efficient dynamics algorithm is developed, which is applicable to a wide range of multibody systems, including underactuated systems, branched or tree-topology systems, robots, and walking machines. The dynamics algorithm is differentiated with respect to the input parameters in order to form sensitivity equations. The algorithm makes use of techniques and notation from the theory of Lie groups and Lie algebras, which is reviewed briefly. One of the strengths of our formulation is the ability to easily differentiate the dynamics algorithm with respect to parameters of interest. We demonstrate one important use of our dynamics and sensitivity algorithms by using them to solve difficult optimal control problems for underactuated systems. The algorithms in this paper have been implemented in a software package named Cstorm (Computer simulation tool for the optimization of robot manipulators), which runs from within Matlab and Simulink. It can be downloaded from the website

. Symbolic methods have been used to provide a general user interface in optimization based animation systems. However, previous methods suffer from the exponential growth in the length of the symbolic expressions of the objectives, constraints and their derivatives. In this paper, we present a symbolic language which is general enough to represent common kinematic and dynamic quantities. The evaluation of these symbolic expressions and their gradients are as fast as numerical methods. In particular, the computational complexity is only a low degree polynomial compared to exponential growth of previous methods, and the optimum performance is achieved for computing the gradients of the generalized forces by extending Hollerbach's technique of compuing inverse dynamics. Furthermore, in this new language the expressions are usually very small so that they can be easily typed in, therefore this method provides a general and efficient interface to optimization based linked figure animation ...

We describe a robotic system composed of a manipulator and two cameras. We use the vision system to guide the robot hand to a visible target. The camera positions are known only approximately. Our system does not use the details of the kinematics of the manipulator. There is no common frame of reference linking vision system, workspace and robot hand. The stereo vision system gives information in terms of picture coordinates. This information is used to control a three degree of freedom robot manipulator in a straightforward and robust fashion, in terms of lines and points visible in the images. We describe the implementation with which we tested this idea. In a traditional robot vision system, to work out how to move a robot to manipulate an object, the location of that object must be found in terms of a common reference