This book describes the development of an integrated approach for generating the path and gait of realistic hexapod robotic systems. It discusses in detail locomation with straight-ahead, crab and turning motion capabilities in varying terrains, like sloping surfaces, staircases, and various user-defined rough terrains. It also presents computer simulations and validation using Virtual Prototyping (VP) tools and real-world experiments. The book also explores improving solutions by applying the developed nonlinear, constrained inverse dynamics model of the system formulated as a coupled dynamical problem based on the Newton–Euler (NE) approach and taking into account realistic environmental conditions. The approach is developed on the basis of rigid multi-body modelling and the concept that there is no change in the configuration of the system in the short time span of collisions.

The volume contains 19 contributions by international experts in the field of multibody system dynamics, robotics and control. The book aims to bridge the gap between the modeling of mechanical systems by means of multibody dynamics formulations and robotics. In the classical approach, a multibody dynamics model contains a very high level of detail, however, the application of such models to robotics or control is usually limited. The papers aim to connect the different scientific communities in multibody dynamics, robotics and control. Main topics are flexible multibody systems, humanoid robots, elastic robots, nonlinear control, optimal path planning, and identification.

Robot and Multibody Dynamics: Analysis and Algorithms provides a comprehensive and detailed exposition of a new mathematical approach, referred to as the Spatial Operator Algebra (SOA), for studying the dynamics of articulated multibody systems. The approach is useful in a wide range of applications including robotics, aerospace systems, articulated mechanisms, bio-mechanics and molecular dynamics simulation. The book also: treats algorithms for simulation, including an analysis of complexity of the algorithms, describes one universal, robust, and analytically sound approach to formulating the equations that govern the motion of complex multi-body systems, covers a range of more advanced topics including under-actuated systems, flexible systems, linearization, diagonalized dynamics and space manipulators. Robot and Multibody Dynamics: Analysis and Algorithms will be a valuable resource for researchers and engineers looking for new mathematical approaches to finding engineering solutions in robotics and dynamics.

Efficient Dynamic Simulation of Robotic Mechanisms presents computationally efficient algorithms for the dynamic simulation of closed-chain robotic systems. In particular, the simulation of single closed chains and simple closed-chain mechanisms is investigated in detail. Single closed chains are common in many applications, including industrial assembly operations, hazardous remediation, and space exploration. Simple closed-chain mechanisms include such familiar configurations as multiple manipulators moving a common load, dexterous hands, and multi-legged vehicles. The efficient dynamics simulation of these systems is often required for testing an advanced control scheme prior to its implementation, to aid a human operator during remote teleoperation, or to improve system performance. In conjunction with the dynamic simulation algorithms, efficient algorithms are also derived for the computation of the joint space and operational space inertia matrices of a manipulator. The manipulator inertia matrix is a significant component of any robot dynamics formulation and plays an important role in both simulation and control. The efficient computation of the inertia matrix is highly desirable for real-time implementation of robot dynamics algorithms. Several alternate formulations are provided for each inertia matrix. Computational efficiency in the algorithm is achieved by several means, including the development of recursive formulations and the use of efficient spatial transformations and mathematics. All algorithms are derived and presented in a convenient tabular format using a modified form of spatial notation, a six-dimensional vector notation which greatly simplifies the presentation and analysis of multibody dynamics. Basic definitions and fundamental principles required to use and understand this notation are provided. The implementation of the efficient spatial transformations is also discussed in some detail. As a means of evaluating efficiency, the number of scalar operations (multiplications and additions) required for each algorithm is tabulated after its derivation. Specification of the computational complexity of each algorithm in this manner makes comparison with other algorithms both easy and convenient. The algorithms presented in Efficient Dynamic Simulation of Robotic Mechanisms are among the most efficient robot dynamics algorithms available at this time. In addition to computational efficiency, special emphasis is also placed on retaining as much physical insight as possible during algorithm derivation. The algorithms are easy to follow and understand, whether the reader is a robotics novice or a seasoned specialist.

This book offers an excellent complementary text for an advanced course on the modelling and dynamic analysis of multi-body mechanical systems, and provides readers an in-depth understanding of the modelling and control of robots. While the Lagrangian formulation is well suited to multi-body systems, its physical meaning becomes paradoxically complicated for single rigid bodies. Yet the most advanced numerical methods rely on the physics of these single rigid bodies, whose dynamic is then given among multiple formulations by the set of the Newton–Euler equations in any of their multiple expression forms. This book presents a range of simple tools to express in succinct form the dynamic equation for the motion of a single rigid body, either free motion (6-dimension), such as that of any free space navigation robot or constrained motion (less than 6-dimension), such as that of ground or surface vehicles. In the process, the book also explains the equivalences of (and differences between) the different formulations.

The 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023. The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows: Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application. Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot. Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots. Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots. Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots. Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics. Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction. Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms. Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.

Khakpour, Zahra M.S.M.E., Purdue University, May 2017. Multibody Dynamics Model of A Full Human Body For Simulating Walking, Major Professor: Hazim El-Mounayri. Bipedal robotics is a relatively new research area which is concerned with creating walking robots which have mobility and agility characteristics approaching those of humans. Also, in general, simulation of bipedal walking is important in many other applications such as: design and testing of orthopedic implants; testing human walking rehabilitation strategies and devices; design of equipment and facilities for human/robot use/interaction; design of sports equipment; and improving sports performance & reducing injury. One of the main technical challenges in that bipedal robotics area is developing a walking control strategy which results in a stable and balanced upright walking gait of the robot on level as well as non-level (sloped/rough) terrains. In this thesis the following aspects of the walking control strategy are developed and tested in a high-fidelity multibody dynamics model of a humanoid body model: 1. Kinematic design of a walking gait using cubic Hermite splines to specify the motion of the center of the foot. 2. Inverse kinematics to compute the legs joint angles necessary to generate the walking gait. 3. Inverse dynamics using rotary actuators at the joints with PD (Proportional-Derivative) controllers to control the motion of the leg links. The thee-dimensional multibody dynamics model is built using the DIS (Dynamic Interactions Simulator) code. It consists of 42 rigid bodies representing the legs, hip, spine, ribs, neck, arms, and head. The bodies are connected using 42 revolute joints with a rotational actuator along with a PD controller at each joint. A penalty normal contact force model along with a polygonal contact surface representing the bottom of each foot is used to model contact between the foot and the terrain. Friction is modeled using an asperity-based friction model which approximates Coulomb friction using a variable anchor-point spring in parallel with a velocity dependent friction law. In this thesis, it is assumed in the model that a balance controller already exists to ensure that the walking motion is balanced (i.e. that the robot does not tip over). A multi-body dynamic model of the full human body is developed and the controllers are designed to simulate the walking motion. This includes the design of the geometric model, development of the control system in kinematics approach, and the simulation setup.