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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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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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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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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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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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Parallel elastic actuation for efficient large payload locomotion

Parallel elastic actuation for efficient large payload locom...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Fabian Günther Yafeng Shu Fumiya Iida Department of Engineering ETH Zurich Zurich Switzerland Bio-Inspired Robotics Lab Institute of Robotics and Intelligent Systems Zurich Switzerland

For legged devices, their ability of carrying payload is a necessity for a wide range of tasks. In this paper, we present a new approach of carrying payload by using a parallel elastic mechanism, which is able to carry payloads of at least 3 times of its bodyweight. Although the robot has no sensory feedback and consists of only two rigid bodies and one spring loaded joint, it is able to achieve efficient and stable forward hopping for a wide range of attached payload. The presented payload carrier ETH Cargo is based on the further development of our platform CHIARO for the payload range between 0 and 100kg. After parameter optimization using simulations, a series of real world experiments prove stable and high efficiency hopping of the prototype over a wide range of payloads.

关键词： Payloads Robots Springs Joints Hip Foot Torque

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Obstacle Avoidance for Kinematically Redundant Robot

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IFAC-PapersOnLine 2015年第28期48卷 490-495页

作者： WANG, Xinyu YANG, Chenguang CHEN, Junshen MA, Hongbin LIU, Feng School of Automation Beijing Institute of Technology Beijing China State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Centre for Robotics and Neural Systems Plymouth University Plymouth United Kingdom College of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Jiaotong University Beijing China

Manipulator's obstacle avoidance is always a challenging topic in robotics. With the concern of the safety problems in human working environment, an improved obstacle avoidance method is proposed based on the general solution of the inverse kinematic problem of a redundant manipulator. A new obstacle detection method using Kinect R sensor is designed to give a robust obstacle information. By designing a parallel system of the manipulator, the proposed control method is not only to achieve the goal of moving away from the obstacle, but also able to guarantee the robot move back to its original pose. The stability of the closed-loop system is established using Lyapunov direct method to ensure the asymptotic stability of the system. The performance of the simulation results verifies the effectiveness of the proposed obstacle detection algorithm and the obstacle avoidance method. © 2015

关键词： Inverse problems Asymptotic stability Closed loop systems Collision avoidance Inverse kinematics Obstacle detectors Redundant manipulators System stability General solutions Inverse kinematic problems Kinematically Redundant Lyapunov direct method Obstacle detection Parallel system Redundant robot Working environment

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System design and locomotion of SUPERball, an untethered tensegrity robot

System design and locomotion of SUPERball, an untethered ten...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Andrew P. Sabelhaus Jonathan Bruce Ken Caluwaerts Pavlo Manovi Roya Fallah Firoozi Sarah Dobi Alice M. Agogino Vytas SunSpiral NASA Ames Intelligent Robotics Group and the Dynamic Tensegrity Robotics Lab CA USA Department of Mechanical Engineering University of California Berkeley USA Department of Computer Engineering University of California Santa Cruz USA Electronics and Information Systems Department Ghent University Oak Ridge TN Belgium

ISBN: (纸本)9781479969241

The Spherical Underactuated Planetary Exploration Robot ball (SUPERball) is an ongoing project within NASA Ames Research Center's intelligent robotics Group and the Dynamic Tensegrity robotics lab (DTRL). The current SUPERball is the first full prototype of this tensegrity robot platform, eventually destined for space exploration missions. This work, building on prior published discussions of individual components, presents the fully-constructed robot. Various design improvements are discussed, as well as testing results of the sensors and actuators that illustrate system performance. Basic low-level motor position controls are implemented and validated against sensor data, which show SUPERball to be uniquely suited for highly dynamic state trajectory tracking. Finally, SUPERball is shown in a simple example of locomotion. This implementation of a basic motion primitive shows SUPERball in untethered control.

关键词： Robots Sensors Power cables Brushless DC motors Actuators

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Where's waldo at time t ? using spatio-temporal models for mobile robot search

Where's waldo at time t ? using spatio-temporal models for m...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Tomáš Krajník Miroslav Kulich Lenka Mudrová Rares Ambrus Tom Duckett Lincoln Centre for Autonomous Systems University of Lincoln Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Intelligent Robotics Lab University of Birmingham UK KTH Royal Institute of Technology Sweden

ISBN: (纸本)9781479969241

We present a novel approach to mobile robot search for non-stationary objects in partially known environments. We formulate the search as a path planning problem in an environment where the probability of object occurrences at particular locations is a function of time. We propose to explicitly model the dynamics of the object occurrences by their frequency spectra. Using this spectral model, our path planning algorithm can construct plans that reflect the likelihoods of object locations at the time the search is performed. Three datasets collected over several months containing person and object occurrences in residential and office environments were chosen to evaluate the approach. Several types of spatio-temporal models were created for each of these datasets and the efficiency of the search method was assessed by measuring the time it took to locate a particular object. The results indicate that modeling the dynamics of object occurrences reduces the search time by 25% to 65% compared to maps that neglect these dynamics.

关键词： Search problems Mobile robots Testing Robot sensing systems Training

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