Rice-obot 1: An intelligent autonomous mobile robot

The Rice-obot I is the first in a series of Intelligent Autonomous Mobile Robots (IAMRs) being developed at Rice University's Cooperative Intelligent Mobile Robots (CIMR) lab. The Rice-obot I is mainly designed to be a testbed for various robotic and AI techniques, and a platform for developing intelligent control systems for exploratory robots. Researchers present the need for a generalized environment capable of combining all of the control, sensory and knowledge systems of an IAMR. They introduce Lisp-Nodes as such a system, and develop the basic concepts of nodes, messages and classes. Furthermore, they show how the control system of the Rice-obot I is implemented as sub-systems in Lisp-Nodes

Human Swarm Interaction: An Experimental Study of Two Types of Interaction with Foraging Swarms

In this paper we present the first study of human-swarm interaction comparing two fundamental types of interaction, coined intermittent and environmental. These types are exemplified by two control methods, selection and beacon control, made available to a human operator to control a foraging swarm of robots. Selection and beacon control differ with respect to their temporal and spatial influence on the swarm and enable an operator to generate different strategies from the basic behaviors of the swarm. Selection control requires an active selection of groups of robots while beacon control exerts an influence on nearby robots within a set range. Both control methods are implemented in a testbed in which operators solve an information foraging problem by utilizing a set of swarm behaviors. The robotic swarm has only local communication and sensing capabilities. The number of robots in the swarm range from 50 to 200. Operator performance for each control method is compared in a series of missions in different environments with no obstacles up to cluttered and structured obstacles. In addition, performance is compared to simple and advanced autonomous swarms. Thirty-two participants were recruited for participation in the study. Autonomous swarm algorithms were tested in repeated simulations. Our results showed that selection control scales better to larger swarms and generally outperforms beacon control. Operators utilized different swarm behaviors with different frequency across control methods, suggesting an adaptation to different strategies induced by choice of control method. Simple autonomous swarms outperformed human operators in open environments, but operators adapted better to complex environments with obstacles. Human controlled swarms fell short of task-specific benchmarks under all conditions. Our results reinforce the importance of understanding and choosing appropriate types of human-swarm interaction when designing swarm systems, in addition to choosing appropriate swarm behaviors

DESIGNING DISTRIBUTED CONTROLLING TESTBED SYSTEM FOR SUPPLY CHAIN AND LOGISTICS IN AUTOMOTIVE INDUSTRY

The arrival of the era of autonomous robots is indisputable. In this paper, innovations in the distributed control systems realized by autonomous guided vehicles in the automotive industry are provided as proof of concept. The main goal of the considered distributed control system design is to bring all-in-one dependent and independent VDA 5050 compliant robots that are easily configurable and manageable with the web-based high-quality user interface responsive business-critical application. Special attention is paid to applying a platform to manage all autonomous IoT based robots in one seamless system. In addition, a "single point of truth" as one of the main issues of modern distributed controlled systems has been considered.

Towards enduring autonomous robots via embodied energy.

Autonomous robots comprise actuation, energy, sensory and control systems built from materials and structures that are not necessarily designed and integrated for multifunctionality. Yet, animals and other organisms that robots strive to emulate contain highly sophisticated and interconnected systems at all organizational levels, which allow multiple functions to be performed simultaneously. Herein, we examine how system integration and multifunctionality in nature inspires a new paradigm for autonomous robots that we call Embodied Energy. Whereas most untethered robots use batteries to store energy and power their operation, recent advancements in energy-storage techniques enable chemical or electrical energy sources to be embodied directly within the structures and materials used to create robots, rather than requiring separate battery packs. This perspective highlights emerging examples of Embodied Energy in the context of developing autonomous robots

Formation control of multiple robots using parametric and implicit representations

A novel method is presented for formation control of a group of autonomous mobile robots using parametric and implicit descriptions of the desired formation. Shape formation is controlled by using potential fields generated from Implicit Polynomial (IP) representations and the control for keeping the desired shape is designed using Elliptical Fourier Descriptors (EFD). Coordination of the robots is modeled by linear springs between each robot and its nearest two neighbors. This approach offers more flexibility in the formation shape and scales well to different swarm sizes and to heterogeneous systems. The method is simulated on robot groups with different sizes to form various formation shapes

A taxonomy for autonomy in industrial autonomous mobile robots including autonomous merchant ships

The concept of autonomous mobile robots (AMR) has gained much popularity in recent years, particularly in commercial settings where the name industrial autonomous mobile robot (IAMR) is proposed. In addition to automatic guided vehicles and automated mining trucks, IAMR also includes autonomous merchant ships. AMR is an old concept which was first introduced in the 1980s. Although the concept of AMRs is old and broadly used, there is still no common definition of autonomy when mobile robots are concerned. This paper will review some of the most known definitions and develop a taxonomy for autonomy in mobile autonomous robots. This will be used to compare the different definitions of robotic autonomy. This paper will mainly look at industrial autonomous mobile robots, i.e. systems that are designed to operate with a clear commercial objective in mind and which are normally supported by a remote control centre. This means that the robot is not fully autonomous, but to varying degrees dependent on humans in some control and monitoring functions.publishedVersio

A one decade survey of autonomous mobile robot systems

Recently, autonomous mobile robots have gained popularity in the modern world due to their relevance technology and application in real world situations. The global market for mobile robots will grow significantly over the next 20 years. Autonomous mobile robots are found in many fields including institutions, industry, business, hospitals, agriculture as well as private households for the purpose of improving day-to-day activities and services. The development of technology has increased in the requirements for mobile robots because of the services and tasks provided by them, like rescue and research operations, surveillance, carry heavy objects and so on. Researchers have conducted many works on the importance of robots, their uses, and problems. This article aims to analyze the control system of mobile robots and the way robots have the ability of moving in real-world to achieve their goals. It should be noted that there are several technological directions in a mobile robot industry. It must be observed and integrated so that the robot functions properly: Navigation systems, localization systems, detection systems (sensors) along with motion and kinematics and dynamics systems. All such systems should be united through a control unit; thus, the mission or work of mobile robots are conducted with reliability

Intelligent Control of Autonomous Six-Legged Robots by Neural Networks

Autonomous mobile six-legged robots are able to demonstrate the potential of intelligent control systems based on recurrent neural networks. The robots evaluate only two forward and two backward looking infrared sensor signals. Fast converging genetic training algorithms are applied to train the robots to move straight in six directions. The robots performed successfully within an obstacle environment and there could be observed a never trained useful interaction between each of the single robots. The paper describes the robot systems and presents the test results. Video clips are downloadable under www.inform.fh-hannover.de/download/lechner.php. Held on IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003, April 2003, Portugal)

The Human Control Over Autonomous Robotic Systems: What Ethical and Legal Lessons for Judicial Uses of AI?

This contribution provides an overview of normative problems posed by increasingly autonomous robotic systems, with the goal of drawing significant lessons for the use of AI technologies in judicial proceedings, especially focusing on the shared control relationship between the human decision-maker (i.e. the judge) and the software system. The exemplary case studies that we zoom in concern two ethically and legally sensitive application domains for robotics: autonomous weapons systems and increasingly autonomous surgical robots. The first case study is expedient to delve into the normative acceptability issue concerning autonomous decision-making and action by robots. The second case study is used to investigate the human responsibility issue in human-robot shared control regimes. The convergent implications of both case studies for the analysis of ethical and legal issues raised by judicial applications of AI enable one to highlight the need for and core contents of a genuinely meaningful human control to be exerted on the operational autonomy, if any, of AI systems in judicial proceedings

Research and development at ORNL/CESAR towards cooperating robotic systems for hazardous environments

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of position and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace