I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

INTRODUCTION: Brief History. Multifingered Hands and Dextrous Manipulation. Outline of the Book. Bibliography. RIGID BODY MOTION: Rigid Body Transformations. Rotational Motion in R3. Rigid Motion in R3. Velocity of a Rigid Body. Wrenches and Reciprocal Screws. MANIPULATOR KINEMATICS: Introduction. Forward Kinematics. Inverse Kinematics. The Manipulator Jacobian. Redundant and Parallel Manipulators. ROBOT DYNAMICS AND CONTROL: Introduction. Lagrange's Equations. Dynamics of Open-Chain Manipulators. Lyapunov Stability Theory. Position Control and Trajectory Tracking. Control of Constrained Manipulators. MULTIFINGERED HAND KINEMATICS: Introduction to Grasping. Grasp Statics. Force-Closure. Grasp Planning. Grasp Constraints. Rolling Contact Kinematics. HAND DYNAMICS AND CONTROL: Lagrange's Equations with Constraints. Robot Hand Dynamics. Redundant and Nonmanipulable Robot Systems. Kinematics and Statics of Tendon Actuation. Control of Robot Hands. NONHOLONOMIC BEHAVIOR IN ROBOTIC SYSTEMS: Introduction. Controllability and Frobenius' Theorem. Examples of Nonholonomic Systems. Structure of Nonholonomic Systems. NONHOLONOMIC MOTION PLANNING: Introduction. Steering Model Control Systems Using Sinusoids. General Methods for Steering. Dynamic Finger Repositioning. FUTURE PROSPECTS: Robots in Hazardous Environments. Medical Applications for Multifingered Hands. Robots on a Small Scale: Microrobotics. APPENDICES: Lie Groups and Robot Kinematics. A Mathematica Package for Screw Calculus. Bibliography. Index Each chapter also includes a Summary, Bibliography, and Exercises

http://www.cds.caltech.edu/%7Emurray/books/MLS/pdf/mls94-complete.pdf

A Mathematical Introduction to Robotic Manipulation

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Planning Algorithms: Introductory Material

In this paper, we present a theoretical framework for design and analysis of distributed flocking algorithms. Two cases of flocking in free-space and presence of multiple obstacles are considered. We present three flocking algorithms: two for free-flocking and one for constrained flocking. A comprehensive analysis of the first two algorithms is provided. We demonstrate the first algorithm embodies all three rules of Reynolds. This is a formal approach to extraction of interaction rules that lead to the emergence of collective behavior. We show that the first algorithm generically leads to regular fragmentation, whereas the second and third algorithms both lead to flocking. A systematic method is provided for construction of cost functions (or collective potentials) for flocking. These collective potentials penalize deviation from a class of lattice-shape objects called /spl alpha/-lattices. We use a multi-species framework for construction of collective potentials that consist of flock-members, or /spl alpha/-agents, and virtual agents associated with /spl alpha/-agents called /spl beta/- and /spl gamma/-agents. We show that migration of flocks can be performed using a peer-to-peer network of agents, i.e., "flocks need no leaders." A "universal" definition of flocking for particle systems with similarities to Lyapunov stability is given. Several simulation results are provided that demonstrate performing 2-D and 3-D flocking, split/rejoin maneuver, and squeezing maneuver for hundreds of agents using the proposed algorithms.

/pdf/flocking-for-multi-agent-dynamic-systems-algorithms-and-5efqu9aidp.pdf

Flocking for multi-agent dynamic systems: algorithms and theory

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.

/pdf/design-fabrication-and-control-of-soft-robots-51z07seyl1.pdf

Design, fabrication and control of soft robots

This paper uses Gauss' principle of least constraint to derive the "natural" dynamic equations for redundant manipulators. This approach is the fastest way to the result that the operational space inertia matrix of the manipulator is the natural weighting matrix for the projection used in solving the redundancy problem. Force-controlled robots form a special case of redundant robots, such that the results can be applied straightforwardly to solve the long-standing problem of the "non-invariance" of the selection matrices in the hybrid force/position control paradigm.

/pdf/gauss-principle-and-the-dynamics-of-redundant-and-xmpaxzgfyt.pdf

Gauss' principle and the dynamics of redundant and constrained manipulators

This paper describes the implementation of a robot control architecture designed to combine a manipulation task design environment with a motion controller that uses the operational space formulation to define and implement arm trajectories and object manipulation. The ProVAR desktop manipulation system is an assistive robot for individuals with a severe physical disability, such as quadriplegia as a result of a high-level spinal cord injury. ProVAR allows non-technical operators access to the robot's capabilities through a direct-manipulation simulation/preview user interface. The novel interface concept is based on two built-in characters to play the roles of helpful consultant and down-to-earth robot arm. This team-based interface concept was chosen to maximize user performance and comfort in controlling the inherently complex mechatronic technology. This paper describes our design decisions and rationale.

/pdf/provar-assistive-robot-system-architecture-1811et3gow.pdf

ProVAR assistive robot system architecture

The paper investigates the dynamic characteristics and control of robot systems involving combinations of parallel and serial mechanical structures, e.g. multiple manipulators and macro/micro-manipulators. A framework for the analysis and control of multiple manipulator systems with respect to the dynamic behavior of the manipulated object is developed. A multi-effector/object system is treated as an augmented object representing the total masses and inertias perceived at some operational point. This system is actuated by the total effector forces acting at that point. The allocation of forces is based on the minimization of the total joint actuator efforts. For serial structures, the effective inertial characteristics of a combined macro/micro-manipulator are shown to be dominated by the inertial characteristics of the micro-manipulator. A new approach for a dextrous dynamic coordination of such mechanisms based on treating the combined system as a single redundant manipulator while minimizing of the deviation from the neutral (mid-range) joint positions of the micro-manipulator is proposed.

Augmented Object and Reduced Effective Inertia in Robot Systems

We present a haptic rendering framework that allows the tactile display of complex virtual environments. This framework allows surface constraints, surface shading, friction, texture and other effects to be modeled solely by updating the position of a representative object, the "virtual proxy". This abstraction reduces the task of the haptic servo control loop to the minimization of the error between user's position and that of the proxy. This framework has been implemented in a system that is able to haptically render virtual environments of a complexity that is near and often in excess of the capabilities of current interactive graphic systems.

/pdf/haptic-interaction-in-virtual-environments-2e09nhraj1.pdf

Haptic interaction in virtual environments

Discusses the basic capabilities needed to enable robots to operate in human populated environments for accomplishing both autonomous tasks and human-guided tasks. These capabilities are key to many new emerging robotic applications in service, construction, field, underwater, and space. An important characteristic of these robots is the "assistance" ability they can bring to humans in performing various physical tasks. To interact with humans and operate in their environments, these robots must be provided with the functionality of mobility and manipulation. The article presents developments of models, strategies, and algorithms concerned with a number of autonomous capabilities that are essential for robot operations in human environments. These capabilities include: integrated mobility and manipulation, cooperative skills between multiple robots, interaction ability with humans, and efficient techniques for real-time modification of collision-free path. These capabilities are demonstrated on two holonomic mobile platforms designed and built at Stanford University in collaboration with Oak Ridge National Laboratories and Nomadic Technologies.

/pdf/robots-in-human-environments-e9ofyb0yr0.pdf

Oussama Khatib

Papers

Gauss' principle and the dynamics of redundant and constrained manipulators

ProVAR assistive robot system architecture

Augmented Object and Reduced Effective Inertia in Robot Systems

Haptic interaction in virtual environments

Robots in human environments