Gait planning and intelligent control for a quadruped robot

We present a method for designing free gaits for a structurally symmetrical quadruped robot capable of performing statically stable, omnidirectional walking on irregular terrain. The robot＇s virtual model is constructed and a control algorithm is proposed by applying virtual components at some strategic locations. The deliberative-based controller can generate flexible sequences of leg transferences while maintaining walking speed, and choose optimum foothold for moving leg based on integration data of exteroceptive terrain profile. Simulation results are presented to show the gait＇s efficiency and system＇s stability in adapting to an uncertain terrain.     

Gait planning for quadruped robot based on dynamic stability: landing accordance ratio

In this article, the method for increasing dynamic stability of quadruped robot is proposed. Previous researches on dynamic walking of quadruped robots have used only walking pattern called central pattern generator (CPG). In this research, different from walking generation with only CPG, a instinctive stability measure called landing accordance ratio, is proposed and used for increasing dynamic stability. In addition, dynamic balance control and control to adjust walking trajectory for increasing dynamic stability measure is also proposed. Proposed methods are verified with dynamic simulation and a large number of experiments with quadruped robot platform.     

Torso motion control and toe trajectory generation of a trotting quadruped robot based on virtual model control

This article presents an intuitive approach based on virtual model control for robust quadrupedal trotting. The controller consists of two main modules: support phase virtual model control for torso motion control and flight phase virtual model control for flight toe trajectory generation. We mapped the relationship between the joint torques of support legs and the torso forces. And virtual forces are applied to the torso to regulate the attitude, height, and velocities of the torso during support phase. To unify the control law, virtual forces are also applied to flight toes to track the planned trajectories that are designed based on lateral velocity of the torso and contact signals of the legs. Moreover, state machine, terrain estimator, and the high level controller are designed to control the robot trotting. Simulations of quadruped trotting versatilely on flat ground, trotting over stairs and slops as well as the impact recovery are reported to demonstrate the effectiveness and robustness of our controller.     

The effect of motor action and different sensory modalities on terrain classification in a quadruped robot running with multiple gaits

Discriminating or classifying different terrains is an important ability for every autonomous mobile robot. A variety of sensors, preprocessing techniques, and algorithms in different robots were applied. However, little attention was paid to the way sensory data was generated and to the contribution of different sensory modalities. In this work, a quadruped robot traversing different grounds using a variety of gaits is used, equipped with a collection of proprioceptive (encoders on active, and passive compliant joints), inertial, and foot pressure sensors. The effect of different gaits on classification performance is assessed and it is demonstrated that separate terrain classifiers for each motor program should be employed. Furthermore, poor performance of randomly generated motor commands confirms the importance of coordinated behavior on sensory information structuring. The collection of sensors sensitive to active, “tactile”, terrain exploration proved effective. Among the individual modalities, encoders on passive compliant joints delivered best results.     

A harmonic potential field approach for joint planning and control of a rigid,separable nonholonomic,mobile robot

The main objective of this paper is to provide a tool for performing path planning at the servo-level of a mobile robot. The ability to perform, in a provably-correct manner, such a complex task at the servo-level can lead to a large increase in the speed of operation, low energy consumption and high quality of response. Planning has been traditionally limited to the high level controller of a robot. The guidance velocity signal from this stage is usually converted to a control signal using what is known as an electronic speed controller (ESC). This paper demonstrates the ability of the harmonic potential field (HPF) approach to generate a provably-correct, constrained, well-behaved trajectory and control signal for a rigid, nonholonomic robot in a stationary, cluttered environment. It is shown that the HPF-based, servo-level planner can address a large number of challenges facing planning in a realistic situation. The suggested approach migrates the rich and provably-correct properties of the solution trajectories from an HPF planner to those of the robot. This is achieved using a synchronizing control signal whose aim is to align the velocity of the robot in its local coordinates, with that of the gradient of the HPF. The link between the two is made possible by representing the robot using what the paper terms “separable form”. The context-sensitive and goal-oriented control signal used to steer the robot is demonstrated to be well-behaved and robust in the presence of actuator noise, saturation and uncertainty in the parameters. The approach is developed, proofs of correctness are provided and the capabilities of the scheme are demonstrated using simulation results.     

Roombots: A hardware perspective on 3D self-reconfiguration and locomotion with a homogeneous modular robot

In this work we provide hands-on experience on designing and testing a self-reconfiguring modular robotic system, Roombots (RB), to be used among others for adaptive furniture. In the long term, we envision that RB can be used to create sets of furniture, such as stools, chairs and tables that can move in their environment and that change shape and functionality during the day. In this article, we present the first, incremental results towards that long term vision. We demonstrate locomotion and reconfiguration of single and metamodule RB over 3D surfaces, in a structured environment equipped with embedded connection ports. RB assemblies can move around in non-structured environments, by using rotational or wheel-like locomotion. We show a proof of concept for transferring a Roombots metamodule (two in-series coupled RB modules) from the non-structured environment back into the structured grid, by aligning the RB metamodule in an entrapment mechanism. Finally, we analyze the remaining challenges to master the full Roombots scenario, and discuss the impact on future Roombots hardware.     

Modal and transition dwell time computation in switching systems: A set-theoretic approach

We consider a plant the dynamics of which switch among a family of systems. Each of these systems has a single stable equilibrium point. We assume that a constraint region for the state is assigned and we consider the problem of finding suitable limitations on the commutation speed in order to avoid constraints violations, even in the absence of state measurements. We introduce the concepts of modal and transition dwell times which lead to the definition of dwell time vector and dwell time graph (represented by a proper matrix), respectively. The former imposes a minimum permanence time on a discrete mode before commuting, the latter imposes the minimum permanence time on the current mode before switching to a specific new one. Both dwell time vector and dwell time graph can be computed via set-theoretic techniques. When the systems share a single equilibrium state, stability can be assured as a special case. Finally, under the assumption of affine dynamics, non-conservative values are achieved.     

A unified fuzzy logic approach to trajectory planning and inverse kinematics for a fire fighting robot operating in tunnels

In this paper a fuzzy logic approach to automatic trajectory planning and closed-loop inverse kinematics for a robotic system purposely designed to extinguish fires in road and railway tunnels is presented. The robot is composed of a self-cooling monorail vehicle carrying a fire fighting monitor. A fuzzy inference system is adopted for the automatic generation of the task-space trajectory for the robot and to distribute the motion among the available joints in the presence of redundant degrees of mobility. Redundancy also allows assigning additional tasks besides the primary task. Simulation case studies are presented to test the performance of the whole system in a typical intervention scenario.     

Storytelling by a kindergarten social assistive robot: A tool for constructive learning in preschool education

Kindergarten Social Assistive Robotics (KindSAR) is a novel technology that offers kindergarten staff an innovative tool for achieving educational aims through social interaction. Children in a preschool setting have previously been shown to benefit from playing educational games with the KindSAR robot. The experiment presented here was designed to examine how KindSAR can be used to engage preschool children in constructive learning. The basic principle of constructivist education is that learning occurs when the learner is actively involved in a process of knowledge construction. In this study, storytelling was used as a paradigm of a constructive educational activity. An interactive robot served as a teacher assistant by telling prerecorded stories to small groups of children while incorporating song and motor activities in the process. Our results show that the children enjoyed interacting with the robot and accepted its authority. This study demonstrates the feasibility and expected benefits of incorporating KindSAR in preschool education.     

A new approach for dynamic fuzzy logic parameter tuning in Ant Colony Optimization and its application in fuzzy control of a mobile robot

Ant Colony Optimization is a population-based meta-heuristic that exploits a form of past performance memory that is inspired by the foraging behavior of real ants. The behavior of the Ant Colony Optimization algorithm is highly dependent on the values defined for its parameters. Adaptation and parameter control are recurring themes in the field of bio-inspired optimization algorithms. The present paper explores a new fuzzy approach for diversity control in Ant Colony Optimization. The main idea is to avoid or slow down full convergence through the dynamic variation of a particular parameter. The performance of different variants of the Ant Colony Optimization algorithm is analyzed to choose one as the basis to the proposed approach. A convergence fuzzy logic controller with the objective of maintaining diversity at some level to avoid premature convergence is created. Encouraging results on several traveling salesman problem instances and its application to the design of fuzzy controllers, in particular the optimization of membership functions for a unicycle mobile robot trajectory control are presented with the proposed method.     

Modeling and analysis of pumps in a wastewater treatment plant: A data-mining approach

A data-mining approach is proposed to model a pumping system in a wastewater treatment plant. Two parameters, energy consumption and wastewater flow rate after the pumping system, are used to evaluate the performance of 27 scenarios while the pump was operating. Five data-mining algorithms are applied to identify the relationships between the outputs (energy consumption and wastewater flow rate) and the inputs (elevation level of the wet well and the speed of the pumps). The accuracy of the flow rate and energy consumption models exceeded 90%. The derived models are deployed to optimize the pump system. The computational results obtained with the proposed models are discussed.     

Cross-docking and milk run logistics in a consolidation network: A hybrid of harmony search and simulated annealing approach

In this paper, we develop a novel integer programming model for the transportation problem of a consolidation network where a set of vehicles are used to transport goods from suppliers to their corresponding customers via three transportation systems: direct shipment, shipment through cross-dock (indirect shipment) and milk run. Since the proposed problem formulation is NP-hard, we offer a hybrid of harmony search (HS) and simulated annealing (SA) based heuristics (HS-SA algorithm) in order to solve the problem. The objective of this problem is to minimize the total shipping cost in the network, so it is tried to reduce the number of required vehicles using an efficient vehicle routing strategy in the algorithm. Solving several numerical examples demonstrates that our solving approach performs much better than GAMS/CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for large size problem instances.     

Estimating job cycle time in a wafer fabrication factory: A novel and effective approach based on post-classification

Estimating job cycle time is an important task for a semiconductor manufacturer as it helps to strengthen relationships with customers and is also conducive to the sustainable development of the manufacturer. The research trend in this field has moved toward the development of hybrid methods, especially those that are classification-based. Most existing methods use pre-classification; however, such methods have several drawbacks, such as incompatibility with the estimation method and unequal sizes of different job groups. In contrast, a post-classification approach has great potential, and therefore is used as a basis for the new approach in this study. In the proposed methodology, a systematic procedure is established to divide jobs into several groups according to their estimation errors. In this way, the classification and estimation stages can be combined seamlessly because they optimize the same objectives. A real case is used to evaluate the effectiveness of the proposed methodology and the experimental results support its superiority over several existing methods. The shortcomings of the existing methods based on pre-classification are also clearly illustrated.     

A multi-scale approach for modeling fire occurrence probability using satellite data and classification trees: A case study in a mountainous Mediterranean region

Fires constitute one major ecological disturbance which influences the natural cycle of vegetation succession and the structure and function of ecosystems. There is no single natural scale at which ecological phenomena are completely understood and thus the capacity to handle scale is beneficial to methodological frameworks for analyzing and monitoring ecosystems. Although satellite imagery has been widely applied for the assessment of fire related topics, there are few studies that consider fire at several spatial scales simultaneously. This research explores the relationships between fire occurrence and several families of environmental factors at different spatial observation scales by means of classification and regression tree models. Predictors accounting for vegetation status (estimated by spectral indices derived from Landsat imagery), fire history, topography, accessibility and vegetation types were included in the models of fire occurrence probability. We defined four scales of analysis by identifying four meaningful thresholds related to fire sizes in the study site. Sampling methodology was based on random points and the power-law distribution describing the local fire regime. The observation scale drastically affected tree size, and therefore the achieved level of detail, and the most explanatory variables in the trees. As a general trend, trees considering all the variables showed a spectral index ruling the most explicative split. According to the comparison of the four pre-determined analysis scales, we propose the existence of three eventual organization levels: landscape patch or ecosystem level, local level and the basic level, the most heterogeneous and complex scale. Rules with three levels of complexity and applicability for management were defined in the tree models: (i) the repeated critical thresholds (predictor values across which fire characteristics change rapidly), (ii) the meaningful final probability classes and (iii) the trees themselves.     

Path-based approach to integrated planning and control for robotic systems: A path-based approach provides an analytical integration of robot planning and control. As a result, the task level control can be achieved, and the system is capable of coping with unexpected or uncertain events

Our newly developed event-based planning and control theory is applied to robotic systems. It Introduces a suitable action or motion reference variable other than time, but directly related to the desired and measurable systems output, called event. Here the event is the length of the path tracked by a robot. It enables the construction of an integrated planning and control system where planning becomes a real-time closed-loop process. The path-based integration planning and control scheme is exemplified by a single-arm tracking problem. Time and energy optimal motion plans combined with nonlinear feedback control are derived in closed form. To the best of our knowledge, this closed-form solution was not obtained before. The equivalence of path-based and time-based representations of nonlinear feedback control is shown, and an overall system stability criterion has also been obtained. The application of event-based integrated planning and control provides the robotic systems the capability to cope with unexpected and uncertain events in real time, without the need for replanning. The theoretical results are illustrated and verified by experiments.     

A toolkit for the analysis of biomechanical overload and prevention of WMSDs: Criteria,procedures and tool selection in a step-by-step approach

BackgroundWhen studying work related musculoskeletal disorders (WMSDs), various factors (mechanical, organizational, psychophysical, individual) and their interrelationships have been considered to be important in general models for epidemiologic surveys and risk assessment and management. Hence the need for a “holistic” approach towards MSD prevention. On the other hand, considering the widespread presence of these factors and of WMSDs in many work places located in both developed and developing countries, there is a strong demand from OSH agencies and operators for “simple” risk assessment and management tools that can also be used by non-experts.ObjectivesThis paper is one of the main contributions towards a WHO/IEA project for developing a “Toolkit for WMSD prevention” by the TC on MSD of the IEA. The paper focuses on selecting tools at different levels for hazard identification, risk estimation and management. The proposals were primarily developed in this context but they also derive from other converging issues such as the ISO TR 12295 – published in 2014.Methods and criteriaProposals are based on two essential criteria: 1) adoption of a step-by-step approach starting with basic tools and moving to more complex tools only when necessary; 2) factoring in complexity and the presence of multiple influencing factors at every step (although with different degrees of in-depth analysis).ResultsThe proposals include: Step one: identification of preliminary occupational hazards and priority setting via “key-enter” questions (at this step, all potential hazards affecting WMSDs should be considered). Step two: identification of risk factors for WMSDs, consisting of a “quick assessment” and substantially aimed at identifying three possible conditions: acceptable/no consequences; critical/redesign urgently needed; more detailed analysis required. Step three: recognized tools for estimating risk (of WMSDs) are used depending on the outcomes of step two. Examples of such tools include “adaptations” of the Revised NIOSH Lifting Equation, Liberty Mutual Psychophysical Tables, OCRA Checklist, etc. These tools should adequately cover most of the influencing factors.Relevance to industryThe use of a step-by-step approach and validated risk estimation tools, in accordance with international standards, makes it possible to tackle the challenge of simplifying complexity in the assessment of biomechanical overload conditions and in the prevention of WMSDs in enterprises of all sizes, small businesses, agriculture, and in developing countries.     

Holistic approach for problem improvement in health education: A human centred basis. A case study on AIDS prevention and control at a Chinese medical school

In order to cope with the changing health needs in the community, an holistic approach on AIDS prevention and control with particular reference to essential quality was introduced at an educational seminar at Hebei Medical University in China, 1996. We have identified three major points in the present study through learning and research process: 1. The importance of cultural norm for the unification of science and technology is identified for the community approach; 2. community care emphasising human quality provides unity in diversity for educational program; and 3. community control emphasising quality assurance demonstrates the effectiveness for program analysis from the viewpoint of human centred systems.     

GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace

This article proposes a new genetic algorithm (GA) methodology to obtain parsimonious support vector regression (SVR) models capable of predicting highly precise setpoints in a continuous annealing furnace (GA-PARSIMONY). The proposal combines feature selection, model tuning, and parsimonious model selection in order to achieve robust SVR models. To this end, a novel GA selection procedure is introduced based on separate cost and complexity evaluations. The best individuals are initially sorted by an error fitness function, and afterwards, models with similar costs are rearranged according to model complexity measurement so as to foster models of lesser complexity. Therefore, the user-supplied penalty parameter, utilized to balance cost and complexity in other fitness functions, is rendered unnecessary. GA-PARSIMONY performed similarly to classical GA on twenty benchmark datasets from public repositories, but used a lower number of features in a striking 65% of models. Moreover, the performance of our proposal also proved useful in a real industrial process for predicting three temperature setpoints for a continuous annealing furnace. The results demonstrated that GA-PARSIMONY was able to generate more robust SVR models with less input features, as compared to classical GA.     

Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry

In recent years, Industry 4.0 has been introduced as a popular term to describe the trend towards digitisation and automation of the manufacturing environment. Despite its potential benefits in terms of improvements in productivity and quality, this concept has not gained much attention in the construction industry. This development is founded in the fact that the far-reaching implications of the increasingly digitised and automated manufacturing environment are still widely unknown. Against this backdrop, the primary objective of this paper is to explore the state of the art as well as the state of practice of Industry 4.0 relating technologies in the construction industry by pointing out the political, economic, social, technological, environmental and legal implications of its adoption. In this context, we present the results of our triangulation approach, which consists of a comprehensive systematic literature review and case study research, by illustrating a PESTEL framework and a value chain model. Additionally, we provide recommendations for further research within a research agenda.