Force Distribution in Walking Machines Over Rough Terrain

1991 ◽  
Vol 113 (4) ◽  
pp. 754-758 ◽  
Author(s):  
John F. Gardner
Keyword(s):  
Optimization Methods ◽  
Solution Technique ◽  
Force Distribution ◽  
Rough Terrain ◽  
Computationally Efficient ◽  
Walking Machines ◽  
The Ohio State University ◽  
Computationally Intensive ◽  
Important Extension ◽  
Adaptive Suspension

This paper presents a computationally efficient technique for the solution of the force distribution problem in walking machines. It differs from previous techniques in two important respects. First, the formulation of the problem allows for arbitrarily oriented surface normals at the point of contact between the feet and the ground. This is an important extension since the primary purpose of legged vehicles is locomotion on rough terrain. Second, the solution technique allows for the introduction of nonlinear constraints which can be tailored to achieve secondary goals in system performance. An example is presented which is based on the geometry of the Ohio State University Adaptive Suspension Vehicle which indicates that the technique performs favorably when compared to pseudo-inverse and computationally intensive optimization methods.

Efficient computation of force distributions for walking machines on rough terrain

Robotica ◽  
1992 ◽  
Vol 10 (5) ◽  
pp. 427-433 ◽  
Author(s):  
J. F. Gardner
Keyword(s):  
Reaction Force ◽  
Optimal Solution ◽  
Force Distribution ◽  
Rough Terrain ◽  
Efficient Computation ◽  
Distribution Problem ◽  
Optimal Scheme ◽  
Walking Machines ◽  
Computational Resources ◽  
Pseudo Inverse

SUMMARYThe force distribution problem for legged vehicles on rough terrain is considered. A general formulation of the force distribution problem in which the feet contact the ground at arbitrary inclinations, is presented. Three techniques are used to solve the force distribution problem for three representative tasks. The Moore-Penrose pseudo-inverse, a numerical optimization scheme and an approximation to the optimal solution are described. The optimal scheme computes the forces which minimize the maximum ratio of tangential foot reaction force to foot normal force. The approximation is used to achieve certain desirable characteristics of the optimal scheme with considerably less computational resources.

Real-Time Robot Capability Analysis

2005 ◽  
Author(s):  
Chalongrath Pholsiri ◽  
Chetan Kapoor ◽  
Delbert Tesar
Keyword(s):  
Decision Making ◽  
Path Planning ◽  
Real Time ◽  
Computationally Efficient ◽  
New Approach ◽  
Ellipsoid Method ◽  
Capability Analysis ◽  
Computationally Intensive ◽  
Planar Robots

Robot Capability Analysis (RCA) is a process in which force/motion capabilities of a manipulator are evaluated. It is very useful in both the design and operational phases of robotics. Traditionally, ellipsoids and polytopes are used to both graphically and numerically represent these capabilities. Ellipsoids are computationally efficient but tend to underestimate while polytopes are accurate but computationally intensive. This article proposes a new approach to RCA called the Vector Expansion (VE) method. The VE method offers accurate estimates of robot capabilities in real time and therefore is very suitable in applications like task-based decision making or online path planning. In addition, this method can provide information about the joint that is limiting a robot capability at a given time, thus giving an insight as to how to improve the performance of the robot. This method is then used to estimate capabilities of 4-DOF planar robots and the results discussed and compared with the conventional ellipsoid method. The proposed method is also successfully applied to the 7-DOF Mitsubishi PA10-7C robot.

A Decomposition Method for Concurrent Design of Mixed Discrete/Continuous Systems

1993 ◽  
Author(s):  
Jeffrey M. Ford ◽  
Christina L. Bloebaum
Keyword(s):  
Design Process ◽  
Decomposition Method ◽  
Organizational Design ◽  
Method Development ◽  
Minimum Weight ◽  
Optimization Methods ◽  
Continuous Systems ◽  
Computationally Efficient ◽  
Subspace Optimization ◽  
Design Variables

Abstract Interest in Concurrent Engineering (CE) has increased as industry looks for more efficient means of product design. Design optimization methods that facilitate the CE approach are an important aspect of current research. Among the methods that have been proposed is the Concurrent Subspace Optimization (CSSO) method, which allows the optimization problem to be decomposed into coupled subproblems. These subproblems may correspond to the different disciplines involved in the design process or to participating organizational design or manufacturing groups. The decomposition allows each discipline to apply their own optimization criteria to the problem. While this method may not be as computationally efficient as other methods, it allows the design process to conform to the departmental divisions that already exist in industry. The method development to date has focused on continuous systems only. However, problems that can not be modeled as continuous systems, such as those involving the placement of active controllers in CSI applications, would benefit from a method that allows the use of discrete parameters. The paper presents a decomposition method (based on CSSO) for the optimal design of mixed discrete/continuous systems. The method is applied to the design of a composite plate for minimum weight, with design variables contributed from sizing variables (continuous) and material combinations (discrete).

Multimodal Biometric Hand-Off for Robust Unobtrusive Continuous Biometric Authentication

2013 ◽  
pp. 389-409
Author(s):  
P. Daphne Tsatsoulis ◽  
Aaron Jaech ◽  
Robert Batie ◽  
Marios Savvides
Keyword(s):  
Tracking System ◽  
Operation Time ◽  
Face Verification ◽  
Computationally Efficient ◽  
Authorized User ◽  
Continuous Authentication ◽  
Training Stage ◽  
Hand Off ◽  
Authentication System ◽  
Computationally Intensive

Conventional access control solutions rely on a single authentication to verify a user’s identity but do nothing to ensure the authenticated user is indeed the same person using the system afterwards. Without continuous monitoring, unauthorized individuals have an opportunity to “hijack” or “tailgate” the original user’s session. Continuous authentication attempts to remedy this security loophole. Biometrics is an attractive solution for continuous authentication as it is unobtrusive yet still highly accurate. This allows the authorized user to continue about his routine but quickly detects and blocks intruders. This chapter outlines the components of a multi-biometric based continuous authentication system. Our application employs a biometric hand-off strategy where in the first authentication step a strong biometric robustly identifies the user and then hands control to a less computationally intensive face recognition and tracking system that continuously monitors the presence of the user. Using multiple biometrics allows the system to benefit from the strengths of each modality. Since face verification accuracy degrades as more time elapses between the training stage and operation time, our proposed hand-off strategy permits continuous robust face verification with relatively simple and computationally efficient classifiers. We provide a detailed evaluation of verification performance using different pattern classification algorithms and show that the final multi-modal biometric hand-off scheme yields high verification performance.

scholarly journals Hybrid Plasma/Molecular-Dynamics Approach for Efficient XFEL Radiation Damage Simulations

Crystals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 478 ◽  
Author(s):  
Alexander Kozlov ◽  
Andrew V. Martin ◽  
Harry M. Quiney
Keyword(s):  
Molecular Dynamics ◽  
Hybrid Approach ◽  
Laser Pulses ◽  
Computationally Efficient ◽  
Plasma Properties ◽  
Drag Forces ◽  
Plasma State ◽  
Hybrid Plasma ◽  
Computationally Intensive ◽  
Dynamics Simulations

X-ray free-electron laser pulses initiate a complex series of changes to the electronic and nuclear structure of matter on femtosecond timescales. These damage processes include widespread ionization, the formation of a quasi-plasma state and the ultimate explosion of the sample due to Coulomb forces. The accurate simulation of these dynamical effects is critical in designing feasible XFEL experiments and interpreting the results. Current molecular dynamics simulations are, however, computationally intensive, particularly when they treat unbound electrons as classical point particles. On the other hand, plasma simulations are computationally efficient but do not model atomic motion. Here we present a hybrid approach to XFEL damage simulation that combines molecular dynamics for the nuclear motion and plasma models to describe the evolution of the low-energy electron continuum. The plasma properties of the unbound electron gas are used to define modified inter-ionic potentials for the molecular dynamics, including Debye screening and drag forces. The hybrid approach is significantly faster than damage simulations that treat unbound electrons as classical particles, enabling simulations to be performed on large sample volumes.

scholarly journals Theoretical and Experimental Analyses of Tensor-Based Regression and Classification

2016 ◽  
Vol 28 (4) ◽  
pp. 686-715 ◽  
Author(s):  
Kishan Wimalawarne ◽  
Ryota Tomioka ◽  
Masashi Sugiyama
Keyword(s):  
Real Data ◽  
Optimization Methods ◽  
Alternating Direction Method ◽  
Trace Norm ◽  
Method Of Multipliers ◽  
Computationally Efficient ◽  
Learning Methods ◽  
Alternating Direction ◽  
Training Samples ◽  
Tensor Norm

We theoretically and experimentally investigate tensor-based regression and classification. Our focus is regularization with various tensor norms, including the overlapped trace norm, the latent trace norm, and the scaled latent trace norm. We first give dual optimization methods using the alternating direction method of multipliers, which is computationally efficient when the number of training samples is moderate. We then theoretically derive an excess risk bound for each tensor norm and clarify their behavior. Finally, we perform extensive experiments using simulated and real data and demonstrate the superiority of tensor-based learning methods over vector- and matrix-based learning methods.

Local joint control in cooperating manipulator systems - force distribution and global stability

Robotica ◽  
1993 ◽  
Vol 11 (2) ◽  
pp. 111-118 ◽  
Author(s):  
Greg R. Luecke ◽  
John F. Gardner
Keyword(s):  
Industrial Robot ◽  
Kinematic Chain ◽  
Joint Control ◽  
Constrained Motion ◽  
Computationally Efficient ◽  
Open Chain ◽  
Control Laws ◽  
Kinematic Chains ◽  
Computationally Intensive ◽  
Control Forces

SUMMARYAlmost all industrial robot applications in use today are controlled using a control law that is simple and computationally efficient, local joint error feedback. When two or more open chain manipulators cooperate to manipulate the same object - such as in mechanical grippers, walking machines, and cooperating manipulator systems - closed kinematic chain, redundantly actuated mechanisms are formed. Control approaches for this type of system focus on the more computationally intensive computed torque or inverse plant control laws, due to the concern over instability caused by the unspecified distribution of control forces in the redundant actuator space, and due to the constrained motion caused by the closed kinematic chains.

scholarly journals A Computationally Efficient Method for Incorporating Spike Waveform Information into Decoding Algorithms

2015 ◽  
Vol 27 (5) ◽  
pp. 1033-1050 ◽  
Author(s):  
Valérie Ventura ◽  
Sonia Todorova
Keyword(s):  
Data Storage ◽  
Single Neuron ◽  
Spike Sorting ◽  
Computationally Efficient ◽  
Decoding Algorithms ◽  
Computer Interfaces ◽  
Minimal Data ◽  
Computationally Intensive ◽  
Linear Decoding ◽  
Kinematic Information

Spike-based brain-computer interfaces (BCIs) have the potential to restore motor ability to people with paralysis and amputation, and have shown impressive performance in the lab. To transition BCI devices from the lab to the clinic, decoding must proceed automatically and in real time, which prohibits the use of algorithms that are computationally intensive or require manual tweaking. A common choice is to avoid spike sorting and treat the signal on each electrode as if it came from a single neuron, which is fast, easy, and therefore desirable for clinical use. But this approach ignores the kinematic information provided by individual neurons recorded on the same electrode. The contribution of this letter is a linear decoding model that extracts kinematic information from individual neurons without spike-sorting the electrode signals. The method relies on modeling sample averages of waveform features as functions of kinematics, which is automatic and requires minimal data storage and computation. In offline reconstruction of arm trajectories of a nonhuman primate performing reaching tasks, the proposed method performs as well as decoders based on expertly manually and automatically sorted spikes.

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