Intelligent robotic systems: Adaptation, learning, and evolution

Living creatures have evolved and formed ecological systems by adapting to their dynamic environment. Robots also need an adaptability to the dynamic environment. This paper presents methodologies for adaptation, learning, and evolution in robotics. Further the intelligence of a robot emerges as a result of the synthesis of simultaneous processing of perception, decision making, and action. A robotic system requires the whole structure of intelligence, and acquires skill and knowledge through interaction with the dynamic environment by computational intelligence, including neural networks, fuzzy systems, and genetic algorithms. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998     

Art and robotics: sixty years of situated machines

This paper pursues the intertwined tracks of robotics and art since the mid 20th century, taking a loose chronological approach that considers both the devices themselves and their discursive contexts. Relevant research has occurred in a variety of cultural locations, often outside of or prior to formalized robotics contexts. Research was even conducted under the aegis of art or cultural practices where robotics has been pursued for other than instrumental purposes. In hindsight, some of that work seems remarkably prescient of contemporary trends. The context of cultural robotics is a highly charged interdisciplinary test environment in which the theory and pragmatics of technical research confronts the phenomenological realities of physical and social being in the world, and the performative and processual practices of the arts. In this context, issues of embodiment, material instantiation, structural coupling, and machine sensing have provoked the reconsideration of notions of (machine) intelligence and cognitivist paradigms. The paradoxical condition of robotics vis-à-vis artificial intelligence is reflected upon. This paper discusses the possibility of a new embodied ontology of robotics that draws upon both cybernetics and post-cognitive approaches.     

Sense-controlled flexible robot behavior

The creation of physical behavior by computational means has been approached differently by industrial and artificial intelligence robotics. Industrial robotics, considering fast response of a robot its most important characteristic, has equipped the robot with predefined, specific behavioral trajectories resulting in fast but inflexible behavior. Artificial intelligence robotics, claiming flexibility as the paramount robot feature, has employed inferred behavior whereby the robot itself determines behavioral patterns for tasks based on the robot's general knowledge about a task domain. Response is now flexible, but the response time is commonly badly degraded. This work defines an action propensity skill which generates flexibleand fast behavior. Flexibility is achieved by attaching perceptions in skills to guide behavior; fast response results from the direct activation of skills. The acquisition and generalization of skills happens under the supervision of a human teacher in an advice-taking mode into which the robot shifts from the execution mode after recognizing lacking competence for a given task. This paper defines such skills, describes an implemented skilled robot system, and discusses some simulation results.     

Trends in the development of sensor systems and their use in some technological areas

The paper describes the trends in the development of sensor systems in the area of robotics. Presented are contact sensors with special emphasis on “skin” sensors for a robot's hand on the basis of piezo-electric materials, such as polyvinylidene fluoride (PVF₂). Among the methods of non-contact sensor perception, vision systems are considered to be most appropriate for robots. Described are industrial vision systems, image processing operations and image recognition. Reference is also made to proximity sensors. The paper further describes robot control systems utilizing sensory information and utilization of artificial intelligence theory in robotics.     

受生物群体智能启发的多机器人系统研究

首先,介绍了生物社会中的群体智能．接着,讨论了群体机器人技术中的群体控制、群体通信和群体形态等主要研究内容及其发展趋势,并介绍了群体机器人系统的几个典型任务环境．最后,通过一个物体搜集任务的仿真实例来说明群体智能设计原则在多机器人系统中的应用．     

Revisiting active perception

Despite the recent successes in robotics, artificial intelligence and computer vision, a complete artificial agent necessarily must include active perception. A multitude of ideas and methods for how to accomplish this have already appeared in the past, their broader utility perhaps impeded by insufficient computational power or costly hardware. The history of these ideas, perhaps selective due to our perspectives, is presented with the goal of organizing the past literature and highlighting the seminal contributions. We argue that those contributions are as relevant today as they were decades ago and, with the state of modern computational tools, are poised to find new life in the robotic perception systems of the next decade.     

PERSPECTIVES ON THE HISTORY OF THE CYBERNETICS MOVEMENT: THE PATH TO CURRENT RESEARCH THROUGH THE CONTRIBUTIONS OF NORBERT WIENER,WARREN McCULLOCH,AND JOHN VON NEUMANN

This is a historical and biographical article that traces the part and life of three of the main pillars of the emergent cybernetics science: Norbert Wiener, Warren McCulloch, and John von Neumann. Though different in their backgrounds, outlook, and scientific work, it is shown how these three main protagonists have jointly erected the cybernetics edifice which now houses robotics, artificial intelligence, automata theory, neural net theory, systems theory, biomedical cybernetics, informatics, and related fields.     

A brief review of affordance in robotic manipulation research

Abstract

This paper presents a brief review of affordance research in robotics, with special concentrations on its applications in grasping and manipulation of objects. The concept of affordance could be a key to realize human-like advanced manipulation intelligence. First, we discuss the concept of affordance while associating with the applications in robotics. Then, we intensively explore the studies that utilize affordance for robotic manipulation applications, such as object recognition, grasping, and object manipulation including tool-use. They obtain and use affordance by several ways like learning from human, using simulation, and real-world execution. Moreover, we show our current work, which is a cloud database for advanced manipulation intelligence. The database accumulates various data related to manipulation task execution and will be an open platform to leverage various affordance techniques.     

Swarm-Bot: A New Distributed Robotic Concept

The swarm intelligence paradigm has proven to have very interesting properties such as robustness, flexibility and ability to solve complex problems exploiting parallelism and self-organization. Several robotics implementations of this paradigm confirm that these properties can be exploited for the control of a population of physically independent mobile robots. The work presented here introduces a new robotic concept called swarm-bot in which the collective interaction exploited by the swarm intelligence mechanism goes beyond the control layer and is extended to the physical level. This implies the addition of new mechanical functionalities on the single robot, together with new electronics and software to manage it. These new functionalities, even if not directly related to mobility and navigation, allow to address complex mobile robotics problems, such as extreme all-terrain exploration. The work shows also how this new concept is investigated using a simulation tool (swarmbot3d) specifically developed for quickly designing and evaluating new control algorithms. Experimental work shows how the simulated detailed representation of one s-bot has been calibrated to match the behaviour of the real robot.     

Artistic communication for A-life and robotics

In research concerning communication between machine and man and involving artificial life and robotics today, the realization of sensitive communication produced by introducing an artistic interface is receiving considerable attention. In this paper, we discuss artistic human-like communication research, including the artificial life and robotics research which would become necessary with an increasing need for man-machine communication. I have consulted an artist involved with this theme, a critic in media art, a scientist, and a biologist. Their research will be introduced from their own view points, and will cover artificial intelligence work capable of communicating with humans. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998     

Neurorobotics

The field of neurorobotics encompasses the intersection of computational neuroscience and robotics. The TUM-led neurorobotics subproject of the Human Brain Project is actively researching concepts within the field and developing the tools to allow researchers to fully explore simulated robotics driven by computational neuroscience models. Further, the development of biologically inspired, tendon-driven robotics systems provides a unique research platform. These efforts allow researchers to explore the interesting space from computational neuroscience to intelligent robots and back.     

Artificial intelligence: New jobs from old

The age of artificial intelligence (AI) is upon us, and its effect upon society in the coming years will be noteworthy. Artificial intelligence is a field that encompasses such applications as robotics, expert systems, natural language understanding, speech recognition, and computer vision. The effect of these AI systems upon existing and future job occupations will be important. This paper takes a look at artificial intelligence in terms of the creation of new job categories. Also, the introduction of AI into the organization to better familiarize the employees about AI will be discussed.     

机器意识研究综述

意识问题是尚未解决的重大哲学问题与科学问题.机器意识是人工智能最前沿的研究领域之一.研发意识机器人对于人工智能与机器人学的发展具有重要科学意义与应用价值.本文首先介绍了意识与感受性的相关概念和理论;然后,详细讨论了机器意识的概念与研究分类、实现方法与计算模型,重点论述了实现机器意识的量子方法;最后,总结了机器意识目前面临的困境与未来可能的发展,并给出了一套机器意识总体实现框架.     

Robosemantics: How Stanley the Volkswagen Represents the World

One of the most impressive feats in robotics was the 2005 victory by a driverless Volkswagen Touareg in the DARPA Grand Challenge. This paper discusses what can be learned about the nature of representation from the car’s successful attempt to navigate the world. We review the hardware and software that it uses to interact with its environment, and describe how these techniques enable it to represent the world. We discuss robosemantics, the meaning of computational structures in robots. We argue that the car constitutes a refutation of semantic arguments against the possibility of strong artificial intelligence.     

Development of a desktop swarm robot system based on pheromone communication

Complex and adaptive population behavior emerges in social insects. In ants, in particular, pheromone communication is the key to understanding their swarm intelligence. This article proposes a swarm robot system based on pheromone communication, and reports on the current status of the development of our robot system. We believe that the system could be used in swarm robotics and complex systems education.     

A computational intelligence perspective on process monitoring and optimization

In the design of autonomous computer-based systems, we often face the embarrassing situation of having to specify, to the system, how it should carry out certain tasks, which involve computations known to be intractable or are suspected of being so. To circumvent such impasses, we resort to complexity-reducing strategies and tactics which trade some loss of accuracy for significant reductions in complexity. The term computational intelligence refers to such complexity reduction methods and to the research aimed at identifying such methods. In this paper we describe briefly some of our own work in this area and then develop a computational intelligence view of the task of process monitoring and optimization, as performed by autonomous systems. Some important current fields of discovery in computational intelligence include neural-net computing, evolutionary programming, fuzzy sets, associative memory and so on.     

Review and reappraisal of human aspects in planning robotic systems

The social issues of worker displacement and worker retraining due to introduction of robotics are discussed and the impact of industrial robots on organization design and job design are reviewed and safety issues mentioned. The impact of human industrial work performance on designing robotics systems is reviewed with special reference to the range of human performance abilities; human information-processing, memory and decision making capabilities; paced-work; supervisory control of robotics systems; and, social and management impacts of robot diffusion.     

Towards a Theoretical Framework of Autonomous Systems Underpinned by Intelligence and Systems Sciences

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems sciences.This paper explores the intelligent and mathematical foundations of autonomous systems.It focuses on structural and behavioral properties that constitute the intelligent power of autonomous systems.It explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive process.The properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems engineering.Emerging paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are described.Advances in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.     

Sensor Fusion and Planning with Perception–Action Network

Robot intelligence requires a real-time connection between sensing and action. A new computation principle of robotics that efficiently implements such a connection is utmost important for the new generation of robotics. In this paper, a perception–action network is presented as a means of efficiently integrating sensing, knowledge, and action for sensor fusion and planning. The network consists of a number of heterogeneous computational units, representing feature transformation and decision-making for action, which are interconnected as a dynamic system. New input stimuli to the network invoke the evolution of network states to a new equilibrium, through which a real-time integration of sensing, knowledge, and action can be accomplished. The network provides a formal, yet general and efficient, method of achieving sensor fusion and planning. This is because the uncertainties of signals, propagated in the network, can be controlled by modifying sensing parameters and robot actions. Algorithms for sensor planning based on the proposed network are established and applied to robot self-localization. Simulation and experimental results are shown.     

Multirobot systems: a classification focused on coordination

Multirobot systems (MRS) are, nowadays, an important research area within robotics and artificial intelligence and a growing number of systems have recently been presented in the literature. Since application domains and tasks that are faced by MRS are of increasing complexity, the ability of the robots to cooperate can be regarded as a fundamental feature. In this paper, we present a survey of the recent work in the area by specifically examining the forms of cooperation and coordination realized in the MRS. In particular, we propose a new taxonomy for classification of the approaches to coordination in MRS and we describe some systems, which we consider representative in our taxonomy. We finally discuss the outcomes of our analysis and try to highlight future trends of the research on MRS.