32920382
Kinematic modeling of head-neck movements
The main objective is to generate kinematic models for the head and neck movements. The motivation comes from our study of individuals with quadriplegia and the need to design rehabilitation aiding devices such as robots and teletheses that can be controlled by head-neck movements. It is then necessary to develop mathematical models for the head and neck movements. Two identification methods have been applied to study the kinematics of head-neck movements of able-body as well as neck-injured subjects. In particular, sagittal plane movements are well modeled by a planar two-revolute-joint linkage. In fact, the motion in joint space seems to indicate that sagittal plane movements may be classified as a single DOF motion. Finally, a spatial three-revolute-joint system has been employed to model 3D head-neck movements.
5542960
Metrics for analysis and optimization of grasps and fixtures
We develop two quality measures for the analysis and optimization of grasps and fixtures. The first metric is a measure of stability and is obtained by analyzing the effect of small perturbations in the position of the grasped object or small disturbance forces on the grasped object The second metric is a measure of robustness to errors in the positions of the fixture elements. In addition, we explore the effect that the stiffness of the fixture elements has on these two quality measures and propose a design optimization approach to maximize stability and robustness to errors.
6879835
Calibrating an air-ground control system from motion correspondences
In this paper we consider the problem of controlling the motion of a vehicle moving on a ground plane based on aerial imagery. In the course of this work we propose a novel analysis of the relationship between the velocity of the vehicle on the ground plane and the velocity of its projection in the image. We show that this relationship provides information about a subset of the parameters of the homography relating the ground plane to the aerial image plane and describe how we can recover this relationship from available measurements.
7023425
A Paradigm for Dynamic Coordination of Multiple Robots
In this paper, we present a paradigm for coordinating multiple robots in the execution of cooperative tasks. The basic idea in the paper is to assign to each robot in the team, a role that determines its actions during the cooperation. The robots dynamically assume and exchange roles in a synchronized manner in order to perform the task successfully, adapting to unexpected events in the environment. We model this mechanism using a hybrid systems framework and apply it in different cooperative tasks: cooperative manipulation and cooperative search and transportation. Simulations and real experiments demonstrating the effectiveness of the proposed paradigm are presented.
29516211
Control of Contact Interactions with Acatastatic Nonholonomic Constraints
A robot arm performs many tasks by interacting with objects or other robots in the environment. It is important for the robot arm to be able to exhibit controlled interactions with the objects and other robots. The contact motion between the robot arm and an object can be rolling, sliding, or separation. In this article, we address the problem of maintaining rolling contact between the robot arm and an external moving object. We assume that a nominal model of the motion of the moving object is available. The dynamic system that characterizes the motion of the robot arm and the moving object in this case is acatastatic and nonholonomic. We have designed a nonlinear feedback for the control of such a system that successfully maintains rolling contact. Simulation results are presented to demonstrate the effectiveness of the system.
15738427
A potential field based approach to multi-robot manipulation
We describe a framework for controlling and coordinating a group of robots for cooperative manipulation tasks. The framework enables a decentralized approach to planning and control. It allows the robots to approach the object, organize themselves into a formation that will trap the object, and then transport the object to the desired destination. Our controllers and planners are derived from simple potential fields and the hierarchical composition of potential fields. We show how these potential field based controllers and planners benefit complex group interactions, specifically for manipulating and transporting objects in the plane. Theoretically, we show how we can derive results on formation stability with potential field based controllers in many cases. Simulation results demonstrate successful application to a wide range of examples without showing sensitivity to parameters. Because the framework is decentralized at both trajectory generation level and the estimation and control agent level, our framework can potentially scale to groups of tens and hundreds of robots.
39362526
Main memory database recovery algorithms and their performance
In main memory systems recovery becomes more complex mainly due to the volatility of main memory and the elimination of the separation of data storage (disk) and data processing locations (main memory). In a disk based database system, it is the disk copy that represents the stable database restored after a system failure; but in MDBSs, the main memory copy of the database must be recovered. The paper discusses the recovery issues in MDBSs and presents a somewhat detailed performance study of two recovery algorithms, one using a shadow approach and the other update-in-place.<<ETX>>
16578484
On the Complexity of Error Explanation
When a system fails to satisfy its specification, the model checker produces an error trace (or counter-example) that demonstrates an undesirable behavior, which is then used in debugging the system. Error explanation is the task of discovering errors in the system or the reasons why the system exhibits the error trace. While there has been considerable recent interest in automating this task and developing tools based on different heuristics, there has been very little effort in characterizing the computational complexity of the problem of error explanation. 
 
In this paper, we study the complexity of two popular heuristics used in error explanation. The first approach tries to compute the smallest number of system changes that need to be made in order to ensure that the given counter-example is no longer exhibited, with the intuition being that these changes are the errors that need fixing. The second approach relies on the observation that differences between correct and faulty runs of a system shed considerable light on the sources of errors. In this approach, one tries to compute the correct trace of the system that is closest to the counter-example. We consider three commonly used abstractions to model programs and systems, namely, finite state Mealy machines, extended finite state machines and pushdown automata. We show that the first approach of trying to find the fewest program changes is NP-complete no matter which of the three formal models is used to represent the system. Moreover we show that no polynomial factor approximation algorithm for computing the smallest set of changes is possible, unless P = NP. For the second approach, we present a polynomial time algorithm that finds the closest correct trace, when the program is represented by a Mealy machine or a pushdown automata. When the program is represented by an extended finite state machine, the problem is once again NP-complete, and no polynomial factor approximation algorithm is likely.
43139382
Data in Your Space
We envision a fully connected data space where flow of data between any two points, is continuous In this paper we discuss the research and development activities for managing this data flow and present our solutions to some of the problems in the areas of mobility, broadcast, web, and security.
42935672
Performance Measurement of Main Memory Database Recovery Algorithms Based on Update-in-Place and Shadow Approaches
The authors present a performance study of two main memory database recovery algorithms, one using a shadow approach and the other update-in-place. The results show that in main memory databases, shadow approach performs better than update-in-place. The authors introduce minor improvements to the shadow scheme and show that the modified algorithm does show further performance improvement. >
16892281
The algorithmics of folding proteins on lattices
It should be possible to predict the fold of a protein into its native conformation, once we are given the sequence of the constituent amino acids. This is known as the protein structure prediction problem and is sometimes referred to as the problem of deciphering the second half of the genetic code. While large proteins fold in nature in seconds, computational chemists and biologists have found that folding proteins to their minimum energy conformations is a challenging unsolved optimization problem. Computational complexity theory has been useful in explaining, at least partially, this (Levinthal's) paradox. The pedagogic cross-disciplinary survey by Ngo, Marks and Karplus (Computational Complexity, Protein Structure Prediction and the Levinthal Paradox, Birkhauser, Basel, 1994) provides an excellent starting point for nonbiologists to take a plunge into the problem of folding proteins. Since then, there has been remarkable progress in the algorithmics of folding proteins on discrete lattice models, an account of which is presented herein.