A new design methodology of electrostrictive actuators for bio-inspired robotics

At present advanced robotics concepts require new and more suitable components to be exploited, especially in the fields of the biomimetic and soft robotics. In this sense, the actuation system represents one of the most limiting factors for the realization of robots with bio-inspired features and performances.This paper presents a new soft actuators based on electroactive polymers (EAPs) technology. The actuator is composed of a pre-stretched silicone film sputtered with a very thin gold film on both sides, working as electrodes. A particular folded geometry, implemented through an innovative fabrication process, allows to exploit the electrostrictive effect and to develop soft actuators suitable in many applications where softness and flexibility are necessary. The manufactured prototypes were developed on the basis of a parametric model that takes into account all geometric parameters and material characteristics. The proposed model is useful to estimate the performances of the actuator and to improve them.     

An auction behavior-based robotic architecture for service robotics

Service robots have the potential of improving the quality of life and assist with people’s daily activities. Such robots must be capable of operating over long periods of time, performing multiple tasks, and scheduling them appropriately for execution. In addition, service robots must be capable of dealing with tasks whose goals may be in conflict with each other and would need to determine, dynamically, which task to pursue in such a case. Adding to the complexity of the problem is the fact that some task requests may have time constraints—deadlines by which the task has to be completed. Given the dynamic nature of the environment, the robots must make decisions on what tasks to pursue in situations where there could be incomplete or missing information. The robots should also be capable of accepting requests for new tasks or services at runtime, while possibly working on another task. In order to achieve these requirements, this paper presents the Auction Behavior-Based Robotic Architecture that brings the following contributions: (1) it uses an auction mechanism to determine the relevance of a task to run at any given time, (2) it handles multiple user requests while dealing with potentially critical time constraints and incomplete information, (3) it enables long-term robot operation and (4) it allows for dynamic assignment of new tasks. The proposed system is validated on a physical robotic platform, the Segway RMP \(^{\circledR }\) and in simulation.     

Intelligent controller modelling for steerable robotic bar using bio-inspired control synthesis

Microsystem Technologies - In any non-linear system, designing and testing the behaviour of a controller is a tedious and time consuming task. Especially balancing the robotic bars or needles under...     

Persuasive robotic assistant for health self-management of older adults: Design and evaluation of social behaviors

Daily health self-management, such as the harmonization of food, exercise and medication, is a major problem for a large group of older adults with obesity or diabetics. Computer-based personal assistance can help to behave healthy by persuading and guiding older adults. For effective persuasion, the assistant should express social behaviors (e.g., turn taking, emotional expressions) to be trustworthy and show empathy. From the motivational interviewing method and synthetic assistants’ literature, we derived a set of social behaviors, and implemented a subset in a physical character, a virtual character and a text interface. The first behavior type concerns conversing with high-level dialogue (semantics, intentions), which could be implemented in all 3 assistants. The other behavior types could only be implemented in the characters: showing natural cues (e.g., gaze, posture), expressing emotions (e.g., compassionate face), and accommodating social conversations (e.g., turn taking). In an experiment, 24 older adults (45–65) interacted with the text interface and one of the characters, conform a “one-week diabetics scenario”. They experienced the virtual and physical character as more empathic and trustworthy than the text-based assistant, and expressed more conversational behavior with the characters. However, it seems that the preference of interacting with the character or the text interface was influenced by the conscientiousness of the participant; more conscientious people liked the text interface better. Older adults responded more negative to the characters that lacked the social behaviors than to the text interface. Some differences between the virtual and physical character probably occurred due to the specific constraints of the physical character.     

Current research in robotics and automation-automated planning andprogramming for robotic batch mechanical assembly

To overcome the difficulties of programming robots, the authors are seeking automatic programming methods, using various forms of computer-based reasoning. This overview outlines their algorithm and software-related research and development for automated mechanical assembly. Five major areas of ongoing research are briefly described: compliant motion; motion planning; machine interpretation of solid models; automatic planning of assembly sequences; and automatic programming of robotic systems     

A view-dependent spatiotemporal saliency-driven approach for time varying volumetric data in geovisualization

Geospatial datasets from satellite observations and model simulations are becoming more accessible. These spatiotemporal datasets are relatively massive for visualization to support advanced analysis and decision making. A challenge to visualizing massive geospatial datasets is identifying critical spatial and temporal changes reflected in the data while maintaining high interactive rendering speed, even when data are accessed remotely. We propose a view-dependent spatiotemporal saliency-driven approach that facilitates the discovery of regions showing high levels of spatiotemporal variability and reduces the rendering intensity of interactive visualization. Our method is based on a novel definition of data saliency, a spatiotemporal tree structure to store visual saliency values, as well as a saliency-driven view-dependent level-of-detail (LOD) control. To demonstrate its applicability, we have implemented the approach with an open-source remote visualization package and conducted experiments with spatiotemporal datasets produced by a regional dust storm simulation model. The results show that the proposed method may not be outstanding in some specific situations, but it consistently performs very well across different settings according to different criteria.     

A taxonomy for multi-agent robotics

A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multi-agent systems according to communication, computational and other capabilities. We survey existing efforts involving multi-agent systems according to their positions in the taxonomy. We also present additional results concerning multi-agent systems, with the dual purposes of illustrating the usefulness of the taxonomy in simplifying discourse about robot collective properties, and also demonstrating that a collective can be demonstrably more powerful than a single unit of the collective.The support of NSERC Canada is greatfully acknowledged.     

A robotics toolbox for MATLAB

The Robotics Toolbox is a software package that allows a MATLAB user to readily create and manipulate datatypes fundamental to robotics such as homogeneous transformations, quaternions and trajectories. Functions provided, for arbitrary serial-link manipulators, include forward and inverse kinematics, Jacobians, and forward and inverse dynamics. This article introduces the Toolbox in tutorial form, with examples chosen to demonstrate a range of capabilities. The complete Toolbox and documentation is freely available via anonymous ftp     

A bio-inspired privacy-preserving framework for healthcare systems

The Journal of Supercomputing - Wireless computing has revolutionized our life with the technological advancement from the traditional networking into a new epoch for communication in ad hoc...     

Towards a safety index for assessing head injury potential in service robotics

There are many standards worldwide dealing with safety issues in robots and adequate protections for their industrial use. Two main safeguard actions are considered to avoid mechanical risks, namely physical or non-physical protections and design guidelines for robots and their components. Nevertheless, there is a lack of specific standards for service robots. Safety in these robots needs a new point of view. It requires a strategy to be changed from pre-contact to post-contact safety, since it is not possible to avoid human–robot interaction. On the other hand, in automotive industry crash test results are used for assessing car safety by means of safety indices. In this paper, quantitative head injury indices for automobiles are analysed and a new safety index for robots NIR is derived. The similitude between NIR and indices used in automotive industry lets the new index to take advantage of previous results and knowledge available in automotive field. Results with NIR are compared with those given by experimental tests with robots. The effects of main parameters on the new index are analysed and results are compared with other safety criteria in order to clarify differences and benefits.     

一种融合DGSOM神经网络的仿生算法研究

基于生理学和脑科学研究成果提出的SOM神经网络仿生优化方法能够通过学习自主绘制出拓扑地图,但需通过大量的尝试确定其初始网络结构,无法保证系统的实时性。提出一种方向信息和特征信息构建的动态增长自组织特征网DGSOM,通过引入方向参数减少网络的训练次数,降低了系统复杂度,通过引入特征参数避免了感知混淆,并将该神经网络模型应用于澳大利亚Milford等提出的RatSLAM模型中。实验表明,提出的DGSOM-RatSLAM模型通过减少视觉细胞的数量降低系统的复杂度;通过视觉细胞的场景匹配实验和位姿细胞的活性状态实验证明该模型能够更快地实现闭环检测,提出的DGSOM-RatSLAM模型的准确率、召回率及F₁值分别为94.74%、86.88%和90.64%,高斯噪声干扰下Gauss-DGSOM-RatSLAM模型的准确率、召回率及F₁值分别为86.70%、80.25%、83.35%。     

A bio-inspired pursuit strategy for optimal control with partially constrained final state

We discuss a biologically inspired cooperative control strategy which allows a group of autonomous systems to solve optimal control problems with free final time and partially constrained final state. The proposed strategy, termed “generalized sampled local pursuit” (GSLP), mimics the way in which ants optimize their foraging trails, and guides the group toward an optimal solution, starting from an initial feasible trajectory. Under GSLP, an optimal control problem is solved in many “short” segments, which are constructed by group members interacting locally with lower information, communication and storage requirements compared to when the problem is solved all at once. We include a series of simulations that illustrate our approach.     

A trust-based bio-inspired approach for credit lending decisions

Credit scoring computation essentially involves taking into account various financial factors and the previous behavior of the credit requesting person. There is a strong degree of correlation between the compliance level and the credit score of a given entity. The concept of trust has been widely used and applied in the existing literature to determine the compliance level of an entity. However it has not been studied in the context of credit scoring literature. In order to address this shortcoming, in this paper we propose a six-step bio-inspired methodology for trust-based credit lending decisions by credit institutions. The proposed methodology makes use of an artificial neural network-based model to classify the (potential) customers into various categories. To show the applicability and superiority of the proposed algorithm, it is applied to a credit-card dataset obtained from the UCI repository. Due to the varying spectrum of trust levels, we are able to solve the problem of binary credit lending decisions. A trust-based credit scoring approach allows the financial institutions to grant credit-based on the level of trust in potential customers.     

A bio-inspired approach for self-correcting compliant assembly systems

Statistical process monitoring and control has been popularized in manufacturing as well as various other industries interested in improving product quality and reducing costs. Advances in this field have focused primarily on more efficient ways for diagnosing faults, reducing variation, developing robust design techniques, and increasing sensor capabilities. However, statistical process monitoring cannot address the need for instant variation reduction during assembly operations. This paper presents a unique dimensional error-compensation approach for compliant sheet metal assembly processes. The resulting autonomous self-correction system integrates rapidly advancing data mining methods, physical models, assembly modeling techniques, sensor capabilities, and actuator networks to implement part-by-part dimensional error compensation. Inspired by biological systems, the proposed quality control approach utilizes immunological principles as a means of developing the required mathematical framework behind the self-correcting methodology. The resulting assembly system obtained through this bio-mimicking approach will be used for autonomous monitoring, detection, diagnosis, and control of station and system level faults, contrary to traditional systems that largely rely on final product measurements and expert analysis to eliminate process faults.     

Testbeds for ubiquitous robotics: A survey

The growing interest in ubiquitous robotics has originated in the last years the development of a high variety of testbeds. This paper presents a survey on existing ubiquitous robotics testbeds comprising networked mobile robots and networks of distributed sensors, cameras and smartphones, among others. The survey provides an insight into the testbed design, internal behavior and use, identifying trends and existing gaps and proposing guidelines for testbed developers. The level of interoperability among different ubiquitous robotics technologies is used as the main conducting criterion of the survey. Other features analyzed include testbed architectures, target experiments and usability tools.     

A robotics wheelchair for crowded public environment

Describes the robotic wheelchair MAid (Mobility Aid for Elderly and Disabled People). MAid's task is to support and transport people with limited motion skills. It is based on a commercial wheelchair that has been equipped with an intelligent control and navigation system. Conversations with disabled and elderly people and with their physicians indicate that the automatic functions desired in a robotic wheelchair do not include following walls or passing doorways, but do include navigation in narrow, cluttered environments and through wide, crowded areas. MAid performs these functions     

RumexWeeds: A grassland dataset for agricultural robotics

Computer vision can lead toward more sustainable agricultural production by enabling robotic precision agriculture. Vision-equipped robots are being deployed in the fields to take care of crops and control weeds. However, publicly available agricultural datasets containing both image data as well as data from navigational robot sensors are scarce. Our real-world dataset RumexWeeds targets the detection of the grassland weeds: Rumex obtusifolius L. and Rumex crispus L. RumexWeeds includes whole image sequences instead of individual static images, which is rare for computer vision image datasets, yet crucial for robotic applications. It allows for more robust object detection, incorporating temporal aspects and considering different viewpoints of the same object. Furthermore, RumexWeeds includes data from additional navigational robot sensors—GNSS, IMU and odometry—which can increase robustness, when additionally fed to detection models. In total the dataset includes 5510 images with 15,519 manual bounding box annotations collected at three different farms and four different days in summer and autumn 2021. Additionally, RumexWeeds includes a subset of 340 ground truth pixels-wise annotations. The dataset is publicly available at https://dtu-pas.github.io/RumexWeeds/ . In this paper we also use RumexWeeds to provide baseline weed detection results considering a state-of-the-art object detector; in this way we are elucidating interesting characteristics of the dataset.     

A survey on coverage path planning for robotics

Coverage Path Planning (CPP) is the task of determining a path that passes over all points of an area or volume of interest while avoiding obstacles. This task is integral to many robotic applications, such as vacuum cleaning robots, painter robots, autonomous underwater vehicles creating image mosaics, demining robots, lawn mowers, automated harvesters, window cleaners and inspection of complex structures, just to name a few. A considerable body of research has addressed the CPP problem. However, no updated surveys on CPP reflecting recent advances in the field have been presented in the past ten years. In this paper, we present a review of the most successful CPP methods, focusing on the achievements made in the past decade. Furthermore, we discuss reported field applications of the described CPP methods. This work aims to become a starting point for researchers who are initiating their endeavors in CPP. Likewise, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works.