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

We address the problem of applying reactive navigation methods for collision avoidance to systems where the dynamics cannot be neglected: mobile robots with slow dynamic capabilities, or systems working at high speeds. Rather than embedding the motion constraints when designing a navigation method, we propose to introduce the robot dynamic constraints directly into the spatial representation. In this space the dynamic capabilities of the robot are implicitly represented. With minor modifications, standard reactive navigation methods can be used in this space implicitly taking into account the robot dynamic constraints. To validate this framework, we show experimental results using two reactive navigation methods whose original formulation do not take the robot dynamic constraints into account (the nearness diagram navigation and the potential field method).

/pdf/reactive-collision-avoidance-for-navigation-with-dynamic-3xj2s6emip.pdf

Reactive collision avoidance for navigation with dynamic constraints

ecently, there has been increasing interest in the emerging field of humancentered robotics. This field focuses on applications such as medical robotics and service robotics, which require close interaction between robotic manipulation systems and human beings, including direct human-manipulator contact. As a result, human-centered robotic systems must consider the requirements of safety in addition to the traditional metrics of performance. To achieve safety we must employ multiple strategies involving all aspects of manipulator design, including the mechanical, electrical, and software architectures. Immediate improvement can often be realized with the use of electronic hardware and software safety mechanisms that intelligently monitor and control manipulator operations. Additional improvements can be realized in the mechanical design. The elimination of pinch points and sharp edges can eliminate the potential for laceration or abrasion injuries. However, the most serious hazard present when working in close proximity with robotic manipulators is the potential for large impact loads, which can result in serious injury or death. To evaluate the potential for serious injury due to impact we can make use of an empirical formula developed by the automotive industry to correlate head acceleration to injury severity known as the head injury criteria (HIC). A simple two-degree-offreedom mass-spring model can be used to predict head accelerations that would occur during an uncontrolled impact. In combination with the HIC index, predicted accelerations are used to estimate the likelihood of serious injury occurring during an impact between a robotic manipulator and a human. For the PUMA 560, an impact velocity of 1 m/s produces a maximum HIC greater than 500, more than enough to cause injury (see Figure 1). [The HIC index is correlated with the maximum abbreviated injury scale (MAIS) to provide a mapping from the calculated HIC values to the likelihood of an occurrence of a specific injury severity level. In Figure 1, HIC values and the corresponding likelihood of a concussive injury (or greater) are shown.] As seen in Figure 1, the addition of a compliant covering can reduce impact loading by an order of magnitude or more. However, the amount of compliant material required to reduce impact loads to a safe level can be substantial. (For the PUMA robot, the required thickness of a compliant cover is more than 5 in, assuming an impact velocity of 1 m/s and an allowable maximum HIC index of 100.) Clearly, adding large amounts of compliant covering is impractical and does not address the root cause of high-impact loads; namely, the large A New Actuation Concept for Human-Friendly Robot Design

/pdf/a-new-actuation-concept-for-human-friendly-robot-design-3n966z4gie.pdf

A New Actuation Concept for Human-Friendly Robot Design

Generating robot motion: the integration of planning and execution

https://cs.stanford.edu/group/manips/publications/pdfs/Khatib_1997_JRAS.pdf

Robot planning and control

Large workspace haptic devices have unique requirements, requiring increased power capabilities along with increased safety considerations. While there are numerous haptic devices available, large workspace systems are hampered by the limitations of current actuation technology. To address this, the Distributed Macro-Mini (DM2) actuation method has been applied to the design of a large workspace haptic device. In this paper, the DM2 method is described and we present experimental results which demonstrate its effectiveness. Finally, the control design is presented along with a discussion of the unique challenges associated with its robustness.

/pdf/large-workspace-haptic-devices-a-new-actuation-approach-cr4ebl43g4.pdf

Oussama Khatib

Papers

Reactive collision avoidance for navigation with dynamic constraints

A New Actuation Concept for Human-Friendly Robot Design

Generating robot motion: the integration of planning and execution

Robot planning and control

Large Workspace Haptic Devices - A New Actuation Approach