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检索条件"机构=Intelligent Systems and Robotics Lab"

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Towards robust online inverse dynamics learning

Towards robust online inverse dynamics learning

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Franziska Meier Daniel Kappler Nathan Ratliff Stefan Schaal CLMC Lab University of Southern California Los Angeles USA Autonomous Motion Department MPI for Intelligent Systems Tubingen Germany Lula Robotics Inc. United States

ISBN: (纸本)9781509037636

Learning of inverse dynamics modeling errors is key for compliant or force control when analytical models are only rough approximations. Thus, designing real time capable function approximation algorithms has been a necessary focus towards the goal of online model learning. However, because these approaches learn a mapping from actual state and acceleration to torque, good tracking is required to observe data points on the desired path. Recently it has been shown how online gradient descent on a simple modeling error offset term to minimize tracking at acceleration level can address this issue. However, to adapt to larger errors a high learning rate of the online learner is required, resulting in reduced compliancy. Thus, here we propose to combine both approaches: The online adapted offset term ensures good tracking such that a nonlinear function approximator is able to learn an error model on the desired trajectory. This, in turn, reduces the load on the adaptive feedback, enabling it to use a lower learning rate. Combined this creates a controller with variable feedback and low gains, and a feedforward model that can account for larger modeling errors. We demonstrate the effectiveness of this framework, in simulation and on a real system.

关键词： inverse kinematics error model on-line model Force control learning rate acceleration ANALYSIS MODELS tracking Learning Controllers

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Part-based Grasp Planning for Familiar Objects

Part-based Grasp Planning for Familiar Objects

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IEEE-RAS International Conference on Humanoid Robots

作者： Nikolaus Vahrenkamp Leonard Westkamp Natsuki Yamanobe Eren E. Aksoy Tamim Asfour High Performance Humanoid Technologies Lab Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany Intelligent Systems Research Institute National Institute of Advanced Industrial Science and Technology (AIST) Japan

ISBN: (纸本)9781509047192

In this work, we present a part-based grasp planning approach that is capable of generating grasps that are applicable to multiple familiar objects. We show how object models can be decomposed according to their shape and local volumetric information. The resulting object parts are labeled with semantic information and used for generating robotic grasping information. We investigate how the transfer of such grasping information to familiar objects can be achieved and how the transferability of grasps can be measured. We show that the grasp transferability measure provides valuable information about how successful planned grasps can be applied to novel object instances of the same object category. We evaluate the approach in simulation, by applying it to multiple object categories and determine how successful the planned grasps can be transferred to novel, but familiar objects. In addition, we present a use case on the humanoid robot ARMAR-III.

关键词： Grasping Planning Shape Semantics Robot sensing systems Training Grasp Manipulator sensing systems Semantics Functional training Portability Planning Shape semiotics

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A Hierarchical Emotion Regulated Sensorimotor Model:Case Studies

A Hierarchical Emotion Regulated Sensorimotor Model:Case Stu...

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第28届中国控制与决策会议

作者： Junpei Zhong Rony Novianto Mingjun Dai Xinzheng Zhang Angelo Cangelosi Centre for Robotics and Neural Systems Plymouth University Laboratory for Intelligent Dynamics and Representation Waseda University Centre of Quantum Computation and Intelligent Systems University of Technology Shenzhen Key Lab of Advanced Communication and Information Processing and Shenzhen Key Laboratory of Media Security Shenzhen University School of Electrical and Information Engineering Jinan University

ISBN: (纸本)9781467397155

Inspired by the hierarchical cognitive architecture and the perception-action model(PAM)[14],we propose that the internal status acts as a kind of common-coding representation which affects,mediates and even regulates the sensorimotor *** regulation can be depicted in the Bayesian framework,that is why cognitive agents are able to generate behaviours with subtle differences according to their emotion or recognize the emotion by perception.A novel recurrent neural network called recurrent neural network with parametric bias units(RNNPB) runs in three modes,constructing a two-level emotion regulated learning model,was further applied to testify this theory in two different cases.

关键词： Embodied Emotion Modelling Cognitive Architecture Recurrent Neural Networks Non-verbal Emotion Expression Social robotics

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Reactive High-level Behavior Synthesis for an Atlas Humanoid Robot

Reactive High-level Behavior Synthesis for an Atlas Humanoid...

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IEEE International Conference on robotics and Automation

作者： Spyros Maniatopoulos Philipp Schillinger Vitchyr Pong David C. Conner Hadas Kress-Gazit Verifiable Robotics Research Group Sibley School of Mechanical and Aerospace Engineering Cornell University Ithaca NY 14853 USA Robert Bosch GmbH Corporate Research Department for Cognitive Systems 70442 Stuttgart Germany Capable Humanitarian Robotics & Intelligent Systems Lab Department of Physics Computer Science and Engineering Christopher Newport University Newport News VA 23606 USA

ISBN: (纸本)9781467380270

In this work, we take a step towards bridging the gap between the theory of formal synthesis and its application to real-world, complex, robotic systems. In particular, we present an end-to-end approach for the automatic generation of code that implements high-level robot behaviors in a verifiably correct manner, including reaction to the possible failures of low-level actions. We start with a description of the system defined a priori. Thus, a non-expert user need only specify a high-level task. We automatically construct a formal specification, in a fragment of Linear Temporal Logic (LTL), that encodes the system's capabilities and constraints, the task, and the desired reaction to low-level failures. We then synthesize a reactive mission plan that is guaranteed to satisfy the formal specification, i.e., achieve the task's goals or correctly react to failures. Lastly, we automatically generate a state machine that instantiates the synthesized symbolic plan in software. We showcase our approach using Team ViGIR's software and Atlas humanoid robot and present lab experiments, thus demonstrating the application of formal synthesis techniques to complex robotic systems. The proposed approach has been implemented and open-sourced as a collection of Robot Operating System (ROS) packages, which are adaptable to other systems.

关键词： Atlas Humanoid Robot formal synthesis ROS

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Multi-stage feature learning based object recognition and 3D pose estimation with kinect 6

Multi-stage feature learning based object recognition and 3D...

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6th International Conference on Information Science and Technology, ICIST 2016

作者： Zeng, Wei Liang, Guoyuan Guangdong, Can Wang Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Dept. Mechanical and Automation Engineering Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781509012206

Impressive achievements have been achieved over the years in object recognition and 3D pose estimation while detecting objects and estimating their 3D poses reliably is still a very challenging problem, especially for texture-less objects in heavily cluttered scenes. In this paper, we introduce an improved approach based on multi-stage feature learning to identify object as well as their 3D orientation efficiently. Our approach is motivated by visual neuroscience models. Currently similar architectures have been successfully applied to pedestrian detection, traffic recognition, face representation, etc. We compute the feature descriptors by multi-stage convolutional neural networks (CNNs) which could map the object identity and 3D poses to the Euclidean distance space by evaluating the similarity between descriptors. By contrast with classical approaches, our method relies on fast and approximate Nearest Neighbor (NN) matching to solve the large scale problems instead of one classifier per object or multi-class classifiers whose complexity grows rapidly with the number of objects. The experiments of detecting poorly-textured objects in cluttered scenarios have been carried out to verify the effectiveness and efficacy of the proposed approach. © 2016 IEEE.

关键词： Object recognition

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Extended Kernel-Based Location Fingerprinting in Wireless Sensor Networks

Extended Kernel-Based Location Fingerprinting in Wireless Se...

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International Conference on Information Fusion

作者： Zhansheng Duan Qi Zhou Uwe D. Hanebeck Center for Info Engr Science Research Xi'an Jiaotong University Shaanxi 710049 China Tencent Corporation Shenzhen Guangdong 518057 China Intelligent Sensor-Actuator-Systems Lab Inst for Anthropomatics and Robotics Karlsruhe Inst of Technology Germany

ISBN: (纸本)9781509020126

Fingerprinting localization is to estimate a mobile terminal's location using its online received signal strength (RSS) measurement and offline RSS database originated from multiple access points (APs). Kernel-based fingerprinting localization is such a competitive algorithm. However, all training data need to be considered in its offline model learning stage. This render high risks for overfitting. To alleviate this, we suggest to apply clustering to the localization region of interest first and then use kernal-based fingerprinting localization for each cluster. A byproduct of clustering is that the computational load for each cluster is also significantly reduced. To further reduce the computational load within each cluster, we also suggest to apply principal component compression to the raw RSS measurements to reduce their dimensionality. The rationale for applying principal component compression is that the distributions of the RSS measurements at all calibration points (CPs) within each cluster will be more similar after clustering. Performance evaluation using both simulated data and real data show that the extended kernel-based fingerprinting localization using clustering and principal component compression have better location estimation accuracy and less computational load.

关键词： Location fingerprinting Received signal strength Overfitting Clustering Principal component compression Dimensionality reduction

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Integrated mechatronics design of flexure joint and controller in dual-drive gantry: a constrained H2 optimization approach

Integrated mechatronics design of flexure joint and controll...

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2017 IEEE International Conference on Advanced intelligent Mechatronics, AIM 2017

作者： Ma, Jun Chen, Si-Lu Kamaldin, Nazir Teo, Chek Sing Tay, Arthur Mamun, Abdullah Al Tan, Kok Kiong Department of Electrical and Computer Engineering SIMTech-NUS Joint Lab on Precision Motion Systems National University of Singapore 117582 Singapore Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore Mechatronics Group Singapore Institute of Manufacturing Technology 138634 Singapore Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo Zhejiang315121 China NUS Grad. School for Inte. Sci. and Eng. and Department of Electrical Computer Engineering National University of Singapore 119077 Singapore

ISBN: (纸本)9781509059980

The dual-drive H gantry is widely used in many industrial processes that require high precision Cartesian motion. The conventional rigid-link version suffers breaking down of joints if any de-synchronization between the two carriages occurs. To prevent above potential risk, a novel biaxial gantry with flexure-links is designed to allow a small rotation angle of the cross-Arm. Nevertheless, the chattering of control signals and inappropriate design of the flexure joint will possibly induce resonant modes of the end effector. Thus, in this work, the design requirements in terms of tracking accuracy, biaxial synchronization, and resonant mode suppression are achieved by integrated optimization of the stiffness of flexures and PID controller parameters for a class of point-To-point trajectories with same dynamics but different steps. From here, an H2 optimization with defined constraints is formulated, and an efficient iterative solver is proposed by hybridizing direct computation of constrained projection gradient and line search of optimal steps. Comparative experiments results obtained on the testbed are presented to verify the effectiveness of proposed method. © 2017 IEEE.

关键词： Constrained optimization

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Whole-body motion planning for humanoid robots with heuristic search

Whole-body motion planning for humanoid robots with heuristi...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Ali Athar Abdul Moeed Zafar Rizwan Asif Armaghan Ahmad Khan Fahad Islam Yasar Osman Hasan Robotics & Intelligent Systems Engineering (RISE) Lab School of Mechanical & Manufacturing Engineering (SMME) National University of Sciences & Technology (NUST) Islamabad Pakistan School of Electrical Engineering & Computer Sciences (SEECS) National University of Sciences & Technology (NUST) Islamabad Pakistan

ISBN: (纸本)9781509037636

The task of whole-body motion planning for humanoid robots is challenging due to its high-DOF nature, stability constraints, and the need for obstacle avoidance and movements that are efficient. Over the years, various approaches have been adopted to solve this problem such as bounding-box models and jacobian-based techniques. More commonly though, sampling-based algorithms are employed for this task since they perform admirably well in high-dimensional spaces. As an alternative, search-based planners offer improvements in terms of optimality and consistency of the solution. However, they are normally considered impractical for high-dimensional motion planning. In this paper, we present a heuristic search-based motion planning framework for humanoid robots that circumvents the drawbacks traditionally associated with search-based planners while catering to the specific requirements of humanoid motion planning. This is achieved primarily through a combination of informative yet computationally inexpensive heuristics, carefully crafted motion primitives as atomic actions, and a whole body inverse kinematics solver for achieving desired end effector orientations. The experimental results show the ability of our framework to perform complex motion planning tasks quickly and efficiently.

关键词： Planning Humanoid robots Collision avoidance Heuristic algorithms Legged locomotion Foot

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Self-adaptive Control Strategy for Exoskeleton to Help Paraplegic Patients Stand Up and Sit Down

Self-adaptive Control Strategy for Exoskeleton to Help Parap...

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第35届中国控制会议

作者： Can Wu Ting Zhang Yongqiang Liao Can Wang Guizhong Wu Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences School of Electro-mechanical Engineering Guangdong University of Technology Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences

ISBN: (纸本)9781509009107

This paper presents a practical control strategy used on lower limb exoskeleton to help paraplegic patients to stand up and sit *** can make the process more comfortable and stable no matter the crutches are pressed heavy or *** is particularly efficient to the robots without drivable ankle joints such SIAT *** space was configured to ensure that the real time-generated trajectory won't break the balance of human-robot *** speed of each joint adjusts to the pressure under the crutches so as to relieve the impact from *** result of experiments shows that the self-adaptive control strategy can not only ensure the stability and fitness,but also form an incentive- "more effort paid,more time saved".

关键词： Exoskeleton Stable space Self-adaptive control Standing up process

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Active tactile object exploration with Gaussian processes

Active tactile object exploration with Gaussian processes

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Zhengkun Yi Roberto Calandra Filipe Veiga Herke van Hoof Tucker Hermans Yilei Zhang Jan Peters Intelligent Autonomous Systems Lab Department of Computer Science Technische Universitat Darmstadt Hochschulstr. 10 64289 Germany School of Mechanical and Aerospace Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 University of Utah Robotics Center School of Computing University of Utah USA

ISBN: (纸本)9781509037636

Accurate object shape knowledge provides important information for performing stable grasping and dexterous manipulation. When modeling an object using tactile sensors, touching the object surface at a fixed grid of points can be sample inefficient. In this paper, we present an active touch strategy to efficiently reduce the surface geometry uncertainty by leveraging a probabilistic representation of object surface. In particular, we model the object surface using a Gaussian process and use the associated uncertainty information to efficiently determine the next point to explore. We validate the resulting method for tactile object surface modeling using a real robot to reconstruct multiple, complex object surfaces.

关键词： Gaussian processes Touch tactile sensors grid point

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