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control of legged robots with optimal distribution of contact forces

Control of legged robots with optimal distribution of contac...

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2011 11th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS 2011

作者： Righetti, Ludovic Buchli, Jonas Mistry, Michael Schaal, Stefan Computational Learning and Motor Control Lab. University of Southern California Los Angeles CA 90089 United States Max Planck Institute for Intelligent Systems Tübingen Germany Dept. of Advanced Robotics Italian Institute of Technology Genoa Italy Disney Research Pittsburgh Pittsburgh PA 15213 United States

ISBN: (纸本)9781612848679

The development of agile and safe humanoid robots require controllers that guarantee both high tracking performance and compliance with the environment. More specifically, the control of contact interaction is of crucial importance for robots that will actively interact with their environment. Model-based controllers such as inverse dynamics or operational space control are very appealing as they offer both high tracking performance and compliance. However, while widely used for fully actuated systems such as manipulators, they are not yet standard controllers for legged robots such as humanoids. Indeed such robots are fundamentally different from manipulators as they are underactuated due to their floating-base and subject to switching contact constraints. In this paper we present an inverse dynamics controller for legged robots that use torque redundancy to create an optimal distribution of contact constraints. The resulting controller is able to minimize, given a desired motion, any quadratic cost of the contact constraints at each instant of time. In particular we show how this can be used to minimize tangential forces during locomotion, therefore significantly improving the locomotion of legged robots on difficult terrains. In addition to the theoretical result, we present simulations of a humanoid and a quadruped robot, as well as experiments on a real quadruped robot that demonstrate the advantages of the controller. © 2011 IEEE.

关键词： controllers

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An approach to accelerate deformable image registration by FPGA based mutual information calculation and pattern search optimization

An approach to accelerate deformable image registration by F...

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IEEE India Conference (INDICON)

作者： Asish Dutta S. Mukhopadhyaya P.S.R. Srinivasa Sastry Control Systems Laboratory Defence Research and Development Organisation Hyderabad India Department of E&ECE Indian Institute of Technology Kharagpur India

Real time computation of deformation fields is essential for automated deformable image registration algorithms for time critical applications. However, the computational power of current microprocessors is not sufficient for real time computation of it; therefore requiring implementations using either massively parallel computers or application-specific hardware accelerators. A sequential pipeline for the calculation of mutual information is presented which allows a faster implementation of deformable image registration process. Hierarchical image subdivision based registration algorithm with mutual information (MI) as the cost function is used. A low memory parallel implementation of MI calculation is proposed here. The final objective of image registration is achieved by a software and hardware implementation, where host computer performs pattern search optimization (PSO) and FPGA calculates MI required for optimization.

关键词： Histograms Mutual information Image registration Entropy Memory management Random access memory Field programmable gate arrays

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Determination and optimization of reinforcement learning parameters for driver actions in traffic

Determination and optimization of reinforcement learning par...

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International Conference on Intelligent Transportation

作者： Linsen Chong Montasir Abbas Bryan Higgs Alejandra Medina C. Y. David Yang Virginia Technology Signal Control & Operation Research and Education Systems Laboratory Virginia Technology USA Virginia Technology USA Virginia Technology Transportation Institute USA Research and Development Turner-Fairbank Highway Research Center USA

An agent-based, artificial intelligence technique known as reinforcement learning has been used to capture vehicle behavior and simulate driver's actions in traffic, especially during emergency situations. This paper discusses the training parameters and their influence on agent simulation performance. A type of agent training technique called Neuro-Fuzzy Actor Critic Reinforcement Learning (NFACRL) is used to test the training parameters with an objective of improving simulation performance. A systematic parameter determination and optimization methodology is provided.

关键词： Vehicles Acceleration Training Learning Optimization Upper bound

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Study of classification of failure states for Small Unmanned Ground Vehicle by response surface methodology

Study of classification of failure states for Small Unmanned...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Young Kook Kim Dooyeol Koh Sang Hoon Lee Soohyun Kim Robotics Program Korea Advanced Institute of Science and Technology Daejeon South Korea Division of Mechanical Engineering School of Mechanical AeroSpace and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon South Korea 5th Research and Development Institute-2 Agency for Defense Development Daejeon South Korea

ISBN: (纸本)9781457707223

SUGV(Small Unmanned Ground Vehicle) used for human rescue and military operation is need to overcome the environment that tough terrains such as a hole or high obstacles. As far as the survival of the vehicle and the preserving ability of the information in the vehicle are concerned, it is essential to have an approach for recognizing unattainable driving states. However, despite the fact that the study of obstacle avoidance and stabilization of SUGV is focused on, it is hardly found out ways of classifying unattainable driving states with the sensors mounted on the SUGV unit. In order to overcome the problem, this paper proposes a practical way for classifying SUGV Failure State(SFS) with the meaningful parameters by statistical method, response surface methodology(RSM).

关键词： Response surface methodology Equations Vehicles Mathematical model Robot sensing systems

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A revised reinforcement learning algorithm to model complicated vehicle continuous actions in traffic

A revised reinforcement learning algorithm to model complica...

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International Conference on Intelligent Transportation

作者： Linsen Chong Montasir Abbas Bryan Higgs Alejandra Medina C. Y. David Yang Virginia Tech Signal Control & Operation Research and Education Systems Lab Virginia Technology USA Virginia Technology USA Transportation Institute Virginia Technology USA Office of Operations Research and Development Turner-Fairbank Highway Research Center USA

An agent-based multi-layer reinforcement learning (RL) framework for naturalistic driving behavior simulation in traffic is introduced. Each agent is a replication of an individual driver. Each agent is implemented by applying artificial intelligence concepts, including: fuzzy logic, neural networks, and reinforcement learning algorithms. A revised Neuro-Fuzzy Actor Critic Reinforcement Learning (NFACRL) is proposed to simulate vehicle actions during safety-critical events when the traffic state is complicated. The revised NFACRL algorithm can handle state dimension problems and continuous vehicle actions.

关键词： Vehicles Learning Acceleration Training Fuzzy sets Firing

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Agent-based evaluation of driver heterogeneous behavior during safety-critical events

Agent-based evaluation of driver heterogeneous behavior duri...

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International Conference on Intelligent Transportation

作者： Montasir Abbas Linsen Chong Bryan Higgs Alejandra Medina C. Y. David Yang Virginia Technology USA Virginia Tech Signal Control & Operation Research and Education Systems Lab Virginia Technology USA Virginia Technology Transportation Institute USA Office of Operations Research and Development Turner-Fairbank Highway Research Center USA

Heterogeneous driver behavior during safety-critical events is more complicated than normal driving situations and is difficult to capture by statistical models. This paper applies an agent-based reinforcement learning method to represent heterogeneous driving behavior for different drivers during safety-critical events. The naturalistic driving data of different drivers during safety-critical events are used in agent training. As an output of the Neuro-Fuzzy Actor Critic Reinforcement Learning (NFACRL) training technique, behavior rules are embedded in different agents to represent heterogeneous actions between drivers. The results show that the NFACRL is able to simulate naturalistic driver behavior and present heterogeneity.

关键词： Vehicles Acceleration Training Estimation Learning Databases

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A Smart Energy system: Distributed resource management, control and optimization

A Smart Energy system: Distributed resource management, cont...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Yong Ding Christian Decker Iana Vassileva Fredrik Wallin Michael Beigl Research Group of Pervasive Computing Systems (TecO) Karlsruhe Institute of Technology Germany INIT AG Germany Research group for Energy Savings Load Control and Energy Efficient Buildings School of Sustainable Development of Society and Technology (HST) Mälardalen University Sweden

This paper presents a novel concept of distributed energy resource and consumption management, which proposes to design a networked and embedded platform for realizing a dynamic energy mix and optimizing the energy consumption dynamically. Based on heterogeneous wireless sensor networks and a local Web of Things platform, the environmental parameters and energy data can be acquired and processed in a distributed manner in real time. In order to improve understanding on how different environmental factors and user behaviors influence the end use of energy, we propose a User Profiling module to investigate the characterization of user's goals and behaviors in terms of energy consumption. Besides the wireless sensor networks, the User Profiling module acquires data also from a questionnaire which mainly concerns four categories, i.e. characteristics of the residents, electrical appliances, attitudes towards energy and building structural information. Furthermore, based on the real-time information from the sensor network platform and the user profiling module, an embedded Resource and Consumption controller will then adapt automatically for instance the regulation processes of energy consumption in a household locally for the users, so that the costs of all energy resources will not exceed the predetermined budget and be regulated in a user-preferred way.

关键词： Energy consumption Energy resources Buildings Multiagent systems Temperature sensors Real time systems Temperature measurement

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Vehicle to grid - Monte Carlo simulations for optimal aggregator strategies

Vehicle to grid - Monte Carlo simulations for optimal aggreg...

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2010 International Conference on Power System Technology: Technological Innovations Making Power Grid Smarter, POWERCON2010

作者： Sandels, Claes Franke, Ulrik Ingvar, Niklas Nordstrom, Lars Hamrén, Roberth Department of Industrial Information and Control Systems Royal Institute of Technology Stockholm Sweden Vattenfall Research and Development Stockholm Sweden

ISBN: (纸本)9781424459407

Previous work has shown that it could be profitable on some control markets to use Plug-in Hybrid Electric Vehicles (PHEV) as control power resources. This concept, where battery driven vehicles such as PHEV s provide ancillary service to the grid is commonly referred to as Vehicle to Grid (V2G). The idea is to sell the capacity and energy of the parked PHEVs on the control market. Due to the fact that cars on average are parked 92% of the day, the availability of this capacity could be very high, even though it will be highly dependent on commuting patterns in peak hours. However, as each PHEV has a very small capacity from a grid perspective, it is necessary to implement an aggregating control system, managing a large number of vehicles. This paper presents strategies for an Aggregator to fulfill control bids on the German control markets. These strategies are tested with respect to reliability, efficiency and profitability in a Monte Carlo simulation model. The model is based on available data on the distributions of commuting departure times and travel distances, as well as average driving power consumption, PHEV battery capacities and the market constraints of the secondary control market in Germany. ©2010 IEEE.

关键词： Plug-in hybrid vehicles

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Switching control of air-fuel ratio in spark ignition engines

Switching control of air-fuel ratio in spark ignition engine...

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作者： Efimov, Denis V. Javaherian, Hosein Nikiforov, Vladimir O. Control of Complex Systems Laboratory Institute of Problems of Mechanical Engineering Saint Petersburg Russia Powertrain Systems Research Laboratory GM Research and Development Center Warren MI United States Department of Information and Control Systems Saint Petersburg State Institute of Information Technology Mechanics and Optics Russia

ISBN: (纸本)9781424474264

The problem of air-fuel ratio (AFR) stabilization in spark ignition engines is addressed in this paper. The proposed strategy consists of proper switching among two control laws to improve the quality of the closed-loop system. The first control law is based on the a priori off-line identified engine model and ensures robust and reliable stabilization of the system at large, while the second control law is adaptive, provides on-line adaptive adjustment to the current fluctuations and improves the accuracy of the closed-loop system. The supervisor realizes the switching rule between these control laws providing better performance for AFR regulation. Results of application are reported and discussed. © 2010 AACC.

关键词： Closed loop systems

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Design of roll autopilot for a tail controlled missile using sliding mode technique

Design of roll autopilot for a tail controlled missile using...

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2010 11th International Workshop on Variable Structure systems, VSS 2010

作者： Parkhi, Prasad Bandyopadhyay, Bijnan Jha, Mahendra IDP in Systems and Control Engineering Indian Institute of Technology Bombay Powai Mumbai-400076 India Armament Research and Development Establishment Pune-411021 India

ISBN: (纸本)9781424458318

Sliding mode design based on Lyapunov matrices is proposed as roll autopilot for a tail controlled missile. The search of Lyapunov matrix for systems with unmatched uncertainties is formulated in terms of linear matrix inequality. The proposed scheme ensures robust roll position control even in the presence of large mismatched parametric uncertainties and external disturbances. The performance of roll autopilot design based on sliding mode technique is compared with the classical autopilot. The simulation results demonstrate that the sliding mode based roll autopilot maintains its performance over wide range of variation of parameters. © 2010 IEEE.

关键词： Linear matrix inequalities

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