An exploration of embodied intelligence and its implications points toward a theory of intelligence in general; with case studies of intelligent systems in ubiquitous computing, business and management, human memory, and robotics. How could the body influence our thinking when it seems obvious that the brain controls the body? In How the Body Shapes the Way We Think, Rolf Pfeifer and Josh Bongard demonstrate that thought is not independent of the body but is tightly constrained, and at the same time enabled, by it. They argue that the kinds of thoughts we are capable of have their foundation in our embodiment-in our morphology and the material properties of our bodies. This crucial notion of embodiment underlies fundamental changes in the field of artificial intelligence over the past two decades, and Pfeifer and Bongard use the basic methodology of artificial intelligence-"understanding by building"-to describe their insights. If we understand how to design and build intelligent systems, they reason, we will better understand intelligence in general. In accessible, nontechnical language, and using many examples, they introduce the basic concepts by building on recent developments in robotics, biology, neuroscience, and psychology to outline a possible theory of intelligence. They illustrate applications of such a theory in ubiquitous computing, business and management, and the psychology of human memory. Embodied intelligence, as described by Pfeifer and Bongard, has important implications for our understanding of both natural and artificial intelligence.

How the Body Shapes the Way We Think: A New View of Intelligence

Also referred to as learning by imitation, tutelage, or apprenticeship learning, Programming by Demonstration (PbD) develops methods by which new skills can be transmitted to a robot. This book examines methods by which robots learn new skills through human guidance. Taking a practical perspective, it covers a broad range of applications, including service robots. The text addresses the challenges involved in investigating methods by which PbD is used to provide robots with a generic and adaptive model of control. Drawing on findings from robot control, human-robot interaction, applied machine learning, artificial intelligence, and developmental and cognitive psychology, the book contains a large set of didactic and illustrative examples. Practical and comprehensive machine learning source codes are available on the books companion website: http://www.programming-by-demonstration.org

Robot Programming by Demonstration

An anthropomorphic hand arm system using variable stiffness actuation has been developed at DLR. It is aimed to reach its human archetype regarding size, weight and performance. The main focus of our development is put on robustness, dynamic performance and dexterity. Therefore, a paradigm change from impedance controlled, but mechanically stiff joints to robots using intrinsic variable compliance joints is carried out.

The DLR hand arm system

The development of robotic cognition and the advancement of understanding of human cognition form two of the current greatest challenges in robotics and neuroscience, respectively. The RobotCub project aims to develop an embodied robotic child (iCub) with the physical (height 90 cm and mass less than 23 kg) and ultimately cognitive abilities of a 2.5-year-old human child. The iCub will be a freely available open system which can be used by scientists in all cognate disciplines from developmental psychology to epigenetic robotics to enhance understanding of cognitive systems through the study of cognitive development. The iCub will be open both in software, but more importantly in all aspects of the hardware and mechanical design. In this paper the design of the mechanisms and structures forming the basic 'body' of the iCub are described. The papers considers kinematic structures dynamic design criteria, actuator specification and selection, and detailed mechanical and electronic design. The paper conclude...

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iCub: the design and realization of an open humanoid platform for cognitive and neuroscience research

Physical human-robot interaction implies the intersection of human and robot workspaces and intrinsically favors collision. The robustness of the most exposed parts, such as the hands, is crucial for effective and complete task execution of a robot. Considering the scales, we think that the robustness can only be achieved by the use of energy storage mechanisms, e.g. in elastic elements. The use of variable stiffness drives provides a low-pass filtering of impacts and allows stiffness adjustments depending on the task. However, using these drive principles does not guarantee the safety of the human due to the dramatically increased dynamics of such system. The design methodology of an antagonistically tendon-driven hand is explained. The resulting hand, very close to its human archetype in terms of size, weight, and, in particular, grasping performance, robustness, and dynamics, is presented. The hyper-actuated hand is a research platform that will also be used to investigate the importance of mechanical couplings and, in future projects, be the basis of a simplified hand that would still perform daily manipulation tasks.

The hand of the DLR Hand Arm System: Designed for interaction

We are trying to realize a humanoid which has flexibility. If humanoids have a flexible structure, safety and posture variety can be achieved. We focus on the role of the human spine and muscle-driven system. By having a flexible spine, a humanoid will have safety and many degrees of freedom to realize a variety of postures. By driving joints by tension-controllable tendons, flexibility of the joints can be controlled. We developed a whole-body tendon-driven flexible-spine humanoid named "Kenta". This paper describes the design and control of Kenta, focusing on the design of the spine. The spine consists of ten joints, vertebrae and rubber disks, ribs, and forty muscles equipped with tension sensors. We also propose control methods of the spine. One uses a geometric virtual robot model and another is based on direct teaching. Using these methods, some whole-body motions are presented.

The design and control of the flexible spine of a fully tendon-driven humanoid "Kenta"

Human can perform variety of limber whole-body motions using numerous muscles and huge number of various sensors. The human brain has all the connections to the sensors and muscles, and learn how to manage them for whole-body motions. In this research, we have aimed to build a complex body with physically massive parallel sensor-motor systems to enter the next stage for studying humanoid brain systems. It is designed to have a flexible spined torso and a whole-body with fully muscle-tendon driven systems. In this paper the design and implementation of the first model of the humanoid is described with some experiments.

Building Spined Muscle-Tendon Humanoid

We propose a concept of reinforceable-muscle humanoid with hyper parallel muscle-tendon systems. By the facilitation of changing the assignment of actuators, we can easily strengthen a specific part of robot body, while changing the arrangement of actuators of current humanoid robots is quite difficult. By developing muscle units in each of which a motor and sensors are integrated, and by adopting musculo-skeletal structure, the rearrangeability of muscles has been realized. This paper describes the concept, prototype design and implementation of the reinforceable muscle humanoid, and the evaluating experiment by a musculo-skeletal humanoid is presented.

Design and implementation of reinforceable muscle humanoid

It is very important and hard to develop motions and behaviors for robots that have complex body and numerous actuators and sensors. The more complex a humanoid's body becomes, the more important the developing environment of the motions and behaviors will be. We have built a fully muscle-driven flexible-spine humanoid named "Kenta", which has 96 actuators and more than 400 sensors including tension sensors, posture sensors, vision sensors, and so on. This paper describes the developing environment of motions and behaviors for the robots like Kenta. A visualizable geometric model, a simulation environment transparent to the real environment, sample procedures of the motion development, and, as an example, realization of swing behavior by Kenta are presented.

Behavior developing environment for the large-DOF muscle-driven humanoid equipped with numerous sensors

Since an environment or body states of robots are very changeable, robotic imitation systems should have ability to develop their behaviors by themselves. For the development of the imitation behaviors, we assume that attention during imitation is the key information. In order to realize such imitation systems with evolving ability, the idea of reinforcement learning system based on the attention structure during imitation has been presented in this paper. First, for describing the attention during imitation behaviors, we define the term 'sensor-action attention pair' as the pair of the most important sensor information and the focused body parts during that behavior. Second, we introduce R-learning, the reinforcement learning method for continual tasks such as imitation behaviors. Third, the method to design the state-action space and the reward function based on the sensor-action attention pair is proposed. At last, for the confirmation of the function of the proposed imitation behavior system, we have done some experiments using actual humanoid Kenta. In those experiments, Kenta can develop imitation behavior that imitates the hand position of the human.

T. Yoshikai

Papers

The design and control of the flexible spine of a fully tendon-driven humanoid "Kenta"

Building Spined Muscle-Tendon Humanoid

Design and implementation of reinforceable muscle humanoid

Behavior developing environment for the large-DOF muscle-driven humanoid equipped with numerous sensors

Development of an imitation behavior in humanoid Kenta with reinforcement learning algorithm based on the attention during imitation