Reactive Balance Control for Legged Robots under Visco-Elastic Contacts

Contacts between robots and environment are often assumed to be rigid for control purposes. This assumption can lead to poor performance when contacts are soft and/or underdamped. However, the problem of balancing on soft contacts has not received much attention in the literature. This paper presents two novel approaches to control a legged robot balancing on visco-elastic contacts, and compares them to other two state-of-the-art methods. Our simulation results show that performance heavily depends on the contact stiffness and the noises/uncertainties introduced in the simulation. Briefly, the two novel controllers performed best for soft/medium contacts, whereas “inverse-dynamics control under rigid-contact assumptions” was the best one for stiff contacts. Admittance control was instead the most robust, but suffered in terms of performance. These results shed light on this challenging problem, while pointing out interesting directions for future investigation.

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Application of neuromuscular electrical stimulation on the support limb during reactive balance control in persons with stroke: a pilot study

Experimental Brain Research ◽

10.1007/s00221-021-06209-2 ◽

2021 ◽

Author(s):

Gonzalo Varas-Diaz ◽

Tanvi Bhatt

Keyword(s):

Electrical Stimulation ◽

Pilot Study ◽

Balance Control ◽

Neuromuscular Electrical Stimulation ◽

Reactive Balance

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Discrete-Time Inverse Dynamics Control of Flexible Joint Robots

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2896519 ◽

1992 ◽

Vol 114 (2) ◽

pp. 229-233 ◽

Cited By ~ 6

Author(s):

K. P. Jankowski ◽

H. Van Brussel

Keyword(s):

Discrete Time ◽

Control Algorithm ◽

Inverse Dynamics ◽

Differential Algebraic Equations ◽

Control Methods ◽

Algebraic Equations ◽

Computationally Efficient ◽

Electromechanical Actuators ◽

Flexible Joint Robots ◽

Inverse Dynamics Control

This paper focuses on the problem of the application of inverse dynamics control methods to robots with flexible joints and electromechanical actuators. Due to drawbacks of the continuous-time inverse dynamics, discussed in the paper, a new control strategy in discrete-time is presented. The proposed control algorithm is based on numerical methods conceived for the solution of index-three systems of differential-algebraic equations. The method is computationally efficient and admits low sampling frequencies. The results of numerical experiments confirm the advantages of the designed control algorithm.

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X-Mark: a benchmark for node-attributed community discovery algorithms

Social Network Analysis and Mining ◽

10.1007/s13278-021-00823-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Salvatore Citraro ◽

Giulio Rossetti

Keyword(s):

State Of The Art ◽

Graph Clustering ◽

Clustering Methods ◽

Community Discovery ◽

Attributed Graphs ◽

Node Labels ◽

Discovery Algorithms ◽

Shed Light

AbstractGrouping well-connected nodes that also result in label-homogeneous clusters is a task often known as attribute-aware community discovery. While approaching node-enriched graph clustering methods, rigorous tools need to be developed for evaluating the quality of the resulting partitions. In this work, we present X-Mark, a model that generates synthetic node-attributed graphs with planted communities. Its novelty consists in forming communities and node labels contextually while handling categorical or continuous attributive information. Moreover, we propose a comparison between attribute-aware algorithms, testing them against our benchmark. Accordingly to different classification schema from recent state-of-the-art surveys, our results suggest that X-Mark can shed light on the differences between several families of algorithms.

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Cortical Engagement Metrics During Reactive Balance Are Associated With Distinct Aspects of Balance Behavior in Older Adults

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2021.684743 ◽

2021 ◽

Vol 13 ◽

Author(s):

Jacqueline A. Palmer ◽

Aiden M. Payne ◽

Lena H. Ting ◽

Michael R. Borich

Keyword(s):

Older Adults ◽

Balance Control ◽

Network Activity ◽

Beta Activity ◽

Balance Function ◽

Potential Biomarker ◽

Beta Power ◽

Wide Range ◽

Motor Cortical ◽

Reactive Balance

Heightened reliance on the cerebral cortex for postural stability with aging is well-known, yet the cortical mechanisms for balance control, particularly in relation to balance function, remain unclear. Here we aimed to investigate motor cortical activity in relation to the level of balance challenge presented during reactive balance recovery and identify circuit-specific interactions between motor cortex and prefrontal or somatosensory regions in relation to metrics of balance function that predict fall risk. Using electroencephalography, we assessed motor cortical beta power, and beta coherence during balance reactions to perturbations in older adults. We found that individuals with greater motor cortical beta power evoked following standing balance perturbations demonstrated lower general clinical balance function. Individual older adults demonstrated a wide range of cortical responses during balance reactions at the same perturbation magnitude, showing no group-level change in prefrontal- or somatosensory-motor coherence in response to perturbations. However, older adults with the highest prefrontal-motor coherence during the post-perturbation, but not pre-perturbation, period showed greater cognitive dual-task interference (DTI) and elicited stepping reactions at lower perturbation magnitudes. Our results support motor cortical beta activity as a potential biomarker for individual level of balance challenge and implicate prefrontal-motor cortical networks in distinct aspects of balance control involving response inhibition of reactive stepping in older adults. Cortical network activity during balance may provide a neural target for precision-medicine efforts aimed at fall prevention with aging.

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Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i05.6503 ◽

2020 ◽

Vol 34 (05) ◽

pp. 9571-9578 ◽

Cited By ~ 1

Author(s):

Wei Zhang ◽

Yue Ying ◽

Pan Lu ◽

Hongyuan Zha

Keyword(s):

State Of The Art ◽

Natural Extension ◽

Target Image ◽

Short Term ◽

Image Representations ◽

High Level ◽

Image Descriptions ◽

Shed Light ◽

Image Caption

Personalized image caption, a natural extension of the standard image caption task, requires to generate brief image descriptions tailored for users' writing style and traits, and is more practical to meet users' real demands. Only a few recent studies shed light on this crucial task and learn static user representations to capture their long-term literal-preference. However, it is insufficient to achieve satisfactory performance due to the intrinsic existence of not only long-term user literal-preference, but also short-term literal-preference which is associated with users' recent states. To bridge this gap, we develop a novel multimodal hierarchical transformer network (MHTN) for personalized image caption in this paper. It learns short-term user literal-preference based on users' recent captions through a short-term user encoder at the low level. And at the high level, the multimodal encoder integrates target image representations with short-term literal-preference, as well as long-term literal-preference learned from user IDs. These two encoders enjoy the advantages of the powerful transformer networks. Extensive experiments on two real datasets show the effectiveness of considering two types of user literal-preference simultaneously and better performance over the state-of-the-art models.

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Reactive balance control in walking based on a bipedal linear inverted pendulum model

2011 IEEE International Conference on Robotics and Automation ◽

10.1109/icra.2011.5980225 ◽

2011 ◽

Cited By ~ 7

Author(s):

Federico Parietti ◽

Hartmut Geyer

Keyword(s):

Inverted Pendulum ◽

Balance Control ◽

Inverted Pendulum Model ◽

Pendulum Model ◽

Reactive Balance

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Persistent Homology, Regimes and Climate Data

10.5194/egusphere-egu21-12462 ◽

2021 ◽

Author(s):

Kristian Strommen ◽

Nina Otter ◽

Matthew Chantry ◽

Joshua Dorrington

Keyword(s):

Dynamical Systems ◽

State Of The Art ◽

Persistent Homology ◽

Topological Invariants ◽

Climate Data ◽

Future Directions ◽

Atlantic Sector ◽

Linear Dynamical Systems ◽

Markovian Dynamics ◽

Shed Light

<p>The concept of weather or climate 'regimes' have been studied since the 70s, to a large extent because of the possibility they offer of truncating complicated dynamics to vastly simpler, Markovian, dynamics. Despite their attraction, detecting them in data is often problematic, and a unified definition remains nebulous. We argue that the crucial common feature across different dynamical systems with regimes is the non-trivial topology of the underlying phase space. Such non-trivial topology can be detected in a robust and explicit manner using persistent homology, a powerful new tool to compute topological invariants in arbitrary datasets. We show some state of the art examples of the application of persistent homology to various non-linear dynamical systems, including real-world climate data, and show how these techniques can shed light on questions such as how many regimes there really are in e.g. the Euro-Atlantic sector. Future directions are also discussed.</p>

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Improved Laplacian Biogeography-Based Optimization Algorithm and Its Application to QAP

Complexity ◽

10.1155/2020/7824785 ◽

2020 ◽

Vol 2020 ◽

pp. 1-19

Author(s):

Xinming Zhang ◽

Doudou Wang ◽

Haiyan Chen ◽

Wentao Mao ◽

Shangwang Liu ◽

...

Keyword(s):

Firefly Algorithm ◽

State Of The Art ◽

Poor Performance ◽

Quadratic Assignment ◽

High Complexity ◽

Computation Complexity ◽

Swarm Optimization ◽

Improved Firefly Algorithm ◽

Complex Functions ◽

Quadratic Assignment Problems

Laplacian Biogeography-Based Optimization (LxBBO) is a BBO variant which improves BBO’s performance largely. When it solves some complex problems, however, it has some drawbacks such as poor performance, weak operability, and high complexity, so an improved LxBBO (ILxBBO) is proposed. First, a two-global-best guiding operator is created for guiding the worst habitat mainly to enhance the exploitation of LxBBO. Second, a dynamic two-differential perturbing operator is proposed for the first two best habitats’ updating to improve the global search ability in the early search phase and the local one in the late search one, respectively. Third, an improved Laplace migration operator is formulated for other habitats’ updating to improve the search ability and the operability. Finally, some measures such as example learning, mutation operation removing, and greedy selection are adopted mostly to reduce the computation complexity of LxBBO. A lot of experimental results on the complex functions from the CEC-2013 test set show ILxBBO obtains better performance than LxBBO and quite a few state-of-the-art algorithms do. Also, the results on Quadratic Assignment Problems (QAPs) show that ILxBBO is more competitive compared with LxBBO, Improved Particle Swarm Optimization (IPSO), and Improved Firefly Algorithm (IFA).

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Software Engineering Productivity

International Journal of Information Technology Project Management ◽

10.4018/jitpm.2011010103 ◽

2011 ◽

Vol 2 (1) ◽

pp. 37-47 ◽

Cited By ~ 1

Author(s):

Adrián Hernández-López ◽

Ricardo Colomo-Palacios ◽

Ángel García-Crespo ◽

Fernando Cabezas-Isla

Keyword(s):

Software Engineering ◽

Influencing Factors ◽

State Of The Art ◽

Research Area ◽

Research Community ◽

Productivity Analysis ◽

Shed Light ◽

Inputs And Outputs

Software engineering productivity has been widely studied, but there are many issues that remain unsolved. Interesting works related to new metrics and more replications of past productivity analysis have emerged, however, in order to fulfill these unsolved issues, a consensus about influencing factors and well recognized and useful sets of inputs and outputs for using in measurements must be reached. In this regard, a clear state of the art may shed light on further research in software engineering productivity, which remains a promising research area. In this paper, general concepts of software engineering productivity along with general issues and recent challenges that need further attention from the research community are presented.

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