Navigation Behavior Selection Using Generalized Stochastic Petri Nets for a Service Robot

Appropriate design and control of behaviors of mobile robots are important for their successful autonomous navigation in a real dynamic environment. This paper proposes a formal selection framework of multiple navigation behaviors for a service robot. In the presented approach, modeling, analysis, and performance evaluation are carried out based on generalized stochastic Petri nets (GSPNs). By adopting a probabilistic approach, the proposed framework helps the robot to select the most desirable navigation behavior in run time according to environmental conditions. Moreover, after mission completion, the robot evaluates its prior navigation performance from accumulated data, and automatically uses the results to improve its future operations. Also, GSPNs have several advantages over direct use of other modeling formalisms such as finite state automata (FSA) or Markov processes (MPs). We conduct experiments on real guidance tasks with visitors by implementing the framework in the guide robot Jinny at the National Science Museum of Korea. The results show that the proposed strategy is useful for a robot's selection of an appropriate navigation behavior in a dynamic environment.     

Balancing control of a single-wheel inverted pendulum system using air blowers: Evolution of Mechatronics capstone design

Inverted pendulum systems are one of typical control systems suitable for cross-disciplinary education. This article delivers the historical evolution of inverted pendulum systems as Mechatronics capstone design projects for undergraduate students. A wheeled inverted pendulum system is quite a challenging and interesting system to appeal students as a design project. Several design examples from two-wheel to one-wheel inverted pendulum system are elaborated. As a current design, a one-wheel inverted pendulum system which is our main contribution, is presented to deliver novel ideas of using air power to balance the system. The roll angle is regulated by air pressure generated from ducted fans while the pitch angle is controlled by a dc motor. Air pressure is controlled by linear control methods to keep the balancing in the roll direction. Experimental studies demonstrate the successful balancing performance.     

Baggage Transportation and Navigation by a Wheeled Inverted Pendulum Mobile Robot

Our goal is to configure an automatic baggage-transportation system by an inverted pendulum robot and realize a navigation function in a real environment. The system consists of two cooperative subsystems: a balancing-and-traveling control subsystem and a navigation subsystem. Position errors of the inverted pendulum robot are often caused by a drift error in the gyro sensor and a change in the center of gravity by a loaded baggage when applying the linear state feedback control method for balancing and traveling. We have reduced the position errors for navigation by resetting the balance position occasionally while traveling with simple methods without an external observer or alternative sensors. In this paper, we state the method and show the experimental results of navigation in a real environment by the implemented robot system.     

一种视觉导航机器人的设计

介绍了一种为机器人添加视觉模块而进行智能导航的设计。主要通过为广茂达AS-UII型机器人添加无线模块将图像信息发至计算机,经图像处理后对机器人进行遥控操作达到闭环控制的目的。此设计价格低廉、运行稳定。     

Neural network based-time optimal sliding mode control for an autonomous underwater robot

This paper presents a robot control system using sliding mode control (SMC) as a core controller. The SMC switches according to the Pontryagin’s time optimal control principle, in which the solution is obtained by using neural network approach. The control system is implemented on Chalawan, a six-degree-of-freedom autonomous underwater robot developed at Mechatronics Laboratory, AIT. The control system can be applied to underwater robots, which have similar kind of architecture. Performance of the proposed controller is compared with various classical SMCs and conventional linear control system. The comparison detail results such as controller performance and error phase portrait are presented and analyzed. Such comparisons ensure the implementation success and prove it as a real time-optimal controller. The results also show the controller’s effective capabilities in plant nonlinearity and parameters uncertainties.     

HERMES - a versatile personal robotic assistant

We have developed a humanoid robot, HERMES, to study several key technologies that are important for personal robots, such as robot design, sensors and perception, locomotion, localization and navigation, manipulation, human-robot communication and interaction, adaptability and learning, system architecture and integration, and dependability. The robot's skill-based system architecture was derived from a qualitative model of human information processing and insights gained from psychological literature dealing with skill acquisition, human performance and motor learning. HERMES' system architecture, several of its skills and the design principles are introduced, and some experiments carried out with the real robot are presented, including a long-term test where HERMES served in a museum, far away from its home laboratory, for more than six months up to 12 hours per day. During this period the robot and its skills were regularly demonstrated to the public by nonexpert presenters. Also, HERMES interacted with the visitors, chatted with them in English, French and German, answered questions and performed services as requested by them.     

Intelligent semi-autonomous vehicles in materials handling

An increase in functionality of semi-autonomous vehicles (SAV) through the implementation of intelligent distributed control and smart sensing techniques is presented. In combination with a modular design approach, this facilitates system modification and improvement, combined with faster customisation of the platform. A distributed and reactive behavioural control architecture is used to realise local autonomous navigation capabilities; improved operator interaction; self protection and safer operation. A virtual engineering environment based on a computer-aided-graphics platform is used (1) for modelling the vehicle and the environment in which it can operate; (2) developing pre-emptive learning and training of responses/behaviours, and (3) for evaluation of vehicle functionality as part of an integrated materials handling system.     

Mechatronic design of a ball-on-plate balancing system

This paper discusses the conception and development of a ball-on-plate balancing system based on mechatronic design principles. Realization of the design is achieved with the simultaneous consideration towards constraints like cost, performance, functionality, extendibility, and educational merit. A complete dynamic system investigation for the ball-on-plate system is presented in this paper. This includes hardware design, sensor and actuator selection, system modeling, parameter identification, controller design and experimental testing. The system was designed and built by students as part of the course Mechatronics System Design at Rensselaer.     

Control of an industrial robot subjected to base mobility

To remove the cell size limitation and to make cellular manufacturing systems more flexible, research has been conducted in which an industrial robot has been given base mobility via an air pallet base and use of existing joint actuators and strategically located, compliant posts. For investigating this new approach of robot mobility within a cell, an appropriate control system has been designed and implemented that interfaces with the standard industrial controller. This paper is a presentation of the resulting control system consisting of multiple-sensor integration into its hierarchical levels. Using the concept of logical sensors, experimental verification is presented for each of the logical sensor subsystems and its successful integration with the existing industrial controller. Experimental results obtained for the fully integrated robot controller illustrate the effectiveness of the multiple-sensor, hierarchical controller for self-propelled mobile robots operating within a manufacturing cell     

Automatisierungstechnik in der Mechatronik — zwei Beispiele aus der Stahlindustrie

Mechatronics, once started as a scientific and industrial experiment, has shown to be a well established scientific discipline with a broad industrial area of applications. Unchanged is the claim of Mechatronics to create a scientific discipline, which offers a new approach to industrial and scientific problems by a synergetic integration of electrical and mechanical engineering with control. Two examples from the field of steel manufacturing systems, namely a hydraulic actuator and a bridle roll device, are chosen in order to demonstrate how one can improve the system performance by linear and nonlinear control. The theory of PCH-systems (port controlled Hamiltonian systems) is used in the nonlinear case, and a combination of partial input-output decoupling and H₂-design is applied to the linear plant. The measurements of the hydraulic actuator and the simulations of the bridle roll system demonstrate the performance of the closed loop. Of course, the presented controllers can easily be used for similar plants. Furthermore, the presented ideas are transferable to similar or related problems in a straightforward manner.     

Sensor fusion for mobile robot navigation

We review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing objects that should be avoided or sought. The review describes integration techniques in two categories: low-level fusion is used for direct integration of sensory data, resulting in parameter and state estimates; high-level fusion is used for indirect integration of sensory data in hierarchical architectures, through command arbitration and integration of control signals suggested by different modules. The review provides an arsenal of tools for addressing this (rather ill-posed) problem in machine intelligence, including Kalman filtering, rule-based techniques, behavior based algorithms, and approaches that borrow from information theory, Dempster-Shafer reasoning, fuzzy logic and neural networks.     

An advanced robot system for automated diagnostic tasks throughpalpation

An approach to the design of a robot system capable of executing complex sensory-motor sequences aimed at gathering data useful for diagnostic purposes is presented. The main features of such a robot system are discussed, and its possible integration in an advanced, interactive expert system for medical diagnosis is considered. As an example of implementation of the concept of a robot system for automated diagnostic tasks, the design characteristics of a tendon-actuated, anthropomorphic finger, incorporating force and position sensors for low-level compliant motion control and skin-like sensors for tactile perception, are outlined. The hierarchical control architecture devised for managing some different diagnostic sensory-motor sequences (subroutines) is also presented     

基于机器视觉的智能导览机器人控制系统设计

在研究机器视觉的移动机器人导航技术的基础上,基于层次结构,简单介绍导览机器人控制系统的总体方案及软硬件设计。采用图像处理中的边缘检测和模板匹配方式进行机器人的视觉导航,使机器人在结构化道路环境下能够自动躲避障碍物,停靠到目标点,并能向参访者导览解说,最后验证了该系统的有效性和优越性。     

Robot path planner based on deep reinforcement learning and the seeker optimization algorithm

Path planning is one of the key technologies for mobile robot applications. However, the traditional robot path planner has a slow planning response, which leads to a long navigation completion time. In this paper, we propose a novel robot path planner (SOA+A2C) that produces global and local path planners with the seeker optimization algorithm (SOA) and the advantage actor-critic (A2C) algorithm, respectively. In addition, to solve the problems of poor convergence performance when training deep reinforcement learning (DRL) agents in complex path planning tasks and path redundancy when metaheuristic algorithms, such as SOA, are used for path planning, we propose the incremental map training method and path de-redundancy method. Simulation results show that first, the incremental map training method can improve the convergence performance of the DRL agent in complex path planning tasks. Second, the path de-redundancy method can effectively alleviate path redundancy without sacrificing the search capability of the metaheuristic algorithm. Third, the SOA+A2C path planner is superior to the Dijkstra & dynamic window approach (Dijkstra+DWA) and the Dijkstra & timed elastic band (Dijkstra+TEB) path planners provided by the robot operating system (ROS) in terms of path length, path planning response time, and navigation completion time. Therefore, the developed SOA+A2C path planner can serve as an effective tool for mobile robot path planning.     

Mechatronics by analogy and application to legged locomotion

A new design methodology for mechatronic systems, dubbed as Mechatronics by Analogy (MbA), is introduced. It argues that by establishing a similarity relation between a complex system and a number of simpler models it is possible to design the former using the analysis and synthesis means developed for the latter. The methodology provides a framework for concurrent engineering of complex systems while maintaining the transparency of the system behavior through making formal analogies between the system and those with more tractable dynamics. The application of the MbA methodology to the design of a monopod robot leg, called the Linkage Leg, is also presented. A series of simulations show that the dynamic behavior of the Linkage Leg is similar to that of a combination of a double pendulum and a spring-loaded inverted pendulum, based on which the system kinematic, dynamic, and control parameters can be designed concurrently.     

Testing real-time embedded systems using high level architecture

This work proposes an environment for testing of heterogeneous embedded systems by means of distributed co-simulation. The test occurs in real-time, co-simulating the system software and hardware platform using the high level architecture (HLA) as a middleware. The novelty of this approach is not only providing support for simulations, but allowing the synchronous integration of heterogeneous simulators with a physical real-time environment. In this work we use the Ptolemy framework as a simulation platform. The approach of co-simulation based on HLA allows different simulators and physical devices to inter-operate, for example robots can operate and be tested with a Ptolemy simulations. Case studies are presented to prove the concept, showing the successful integration between Ptolemy and the HLA and test systems using Robot-in-the-loop. The integration of real-time devices through robot operating system was also presented. The approach proved to be able to detect logical and physical design flaws.     

Reaction-diffusion navigation robot control: from chemical to VLSI analogic processors

We introduce a new methodology and experimental implementations for real-time wave-based robot navigation in a complex, dynamically changing environment. The main idea behind the approach is to consider the robot arena as an excitable medium, in which moving objects-obstacles and the target-are represented by sites of autowave generation: the target generates attractive waves, while the obstacles repulsive ones. The moving robot detects traveling and colliding wave fronts and uses the information about dynamics of the autowaves to adapt its direction of collision-free motion toward the target. This approach allows us to achieve a highly adaptive robot behavior and thus an optimal path along which the robot reaches the target while avoiding obstacles. At the computational and experimental levels, we adopt principles of computation in reaction-diffusion (RD) nonlinear active media. Nonlinear media where autowaves are used for information processing purposes can therefore be considered as RD computing devices. In this paper, we design and experiment with three types of RD processors: experimental and computational Belousov-Zhabotinsky chemical processor, computational CNN processor, and experimental RD-CNN very large-scale integration chip-the complex analog and logic computing engine (CACE1k). We demonstrate how to experimentally implement robot navigation using space-time snapshots of active chemical medium and how to overcome low-speed limitation of this "wetware" implementation in CNN-based silicon processors.     

Development and control of a unicycle robot with double flywheels

Balancing the unicycle robot is a challenging topic for control and mechanical design. The robot has to robustly balance itself in both longitudinal and lateral directions under uncertain disturbances and inherent non-linear effects. This paper presents the development and control of a unicycle robot which utilizes double-flywheel technique for roll (lateral) control and the inverted-pendulum technique for pitch (longitudinal) control. The non-linear dynamic model is derived by Lagrangian approach. The linearized model is approximated around upright position and identified. The unicycle robot prototype is designed and controlled. Linear quadratic regulator with integral action (LQR + I) is proposed to balance the robot in both directions and compared with the conventional LQR. Simulation and experimental results of balancing control and robot position control are presented. The results significantly show superior performance of LQR + I over LQR.     

Modeling, design, and control integration: a necessary step in mechatronics

Future products require more sophistication and flexibility from both the hardware and software points of view. In particular, these products involve several energy domains, which is one reason for the new requirements for system design and the integration of design and control. These are important aspects not only for industrial research and development personnel but also for academicians. In this paper, a modeling and control system perspective relevant to the systems approach and fast adaptive control systems is first presented. Specifically, some of the important aspects are properties from graphical system representation, achievable performance, and fast control algorithms. A few applications are then presented to illustrate some system design requirements and control system characteristics. These applications emphasize the demand for high performance systems which has introduced an increasingly challenging system design problem. The applications discussed include high-speed robot manipulators, high-speed and high-precision magnetic bearing systems, atomic resolution systems, and their control using digital signal processing boards. Experimental results pertaining to the control of a five-axis magnetically levitated turbopump are presented.     

Integrating fuzzy control of the dexterous National Taiwan University (NTU) hand

Compared to traditional tendon-driven robots, the mechanism design of the National Taiwan University hand has an uncoupled configuration and is compact in size. In this paper, a specially designed compact control system, which is embedded into the NTU hand to satisfy the limited space, is developed to perform the control of the five-finger robot with 17 degrees of freedom (DOF). There are total 17 actuators including transmission mechanism, 17 potentiometers, and 18 tactile sensor pads to be integrated. Those 17 actuators should be controlled simultaneously by integrating 17 position sensing signals and 18 tactile signals. Multi-loop position control is further complicated by multi-loop force control as well as sensor integration. The proposed control system distributes the computation load into several modules and utilizes the DSP chip. It takes advantage of the fuzzy control by introducing the knowledge of human and sensor fusion with the finger joint and tactility. Using the communication function of the control system, the knowledge bases can be loaded for high level computation and modified during run time.