41 research outputs found
Climbing and Walking Robots
Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study
Bio-Inspired Robotics
Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field
Computational and Robotic Models of Human Postural Control
Currently, no bipedal robot exhibits fully human-like characteristics in terms of its postural control and movement. Current biped robots move more slowly than humans and are much less stable. Humans utilize a variety of sensory systems to maintain balance, primary among them being the visual, vestibular and proprioceptive systems. A key finding of human postural control experiments has been that the integration of sensory information appears to be dynamically regulated to adapt to changing environmental conditions and the available sensory information, a process referred to as "sensory re-weighting." In contrast, in robotics, the emphasis has been on controlling the location of the center of pressure based on proprioception, with little use of vestibular signals (inertial sensing) and no use of vision. Joint-level PD control with only proprioceptive feedback forms the core of robot standing balance control. More advanced schemes have been proposed but not yet implemented. The multiple sensory sources used by humans to maintain balance allow for more complex sensorimotor strategies not seen in biped robots, and arguably contribute to robust human balance function across a variety of environments and perturbations. Our goal is to replicate this robust human balance behavior in robots.In this work, we review results exploring sensory re-weighting in humans, through a series of experimental protocols, and describe implementations of sensory re-weighting in simulation and on a robot
Hierarchical neural control of human postural balance and bipedal walking in sagittal plane
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 177-192).The cerebrocerebellar system has been known to be a central part in human motion control and execution. However, engineering descriptions of the system, especially in relation to lower body motion, have been very limited. This thesis proposes an integrated hierarchical neural model of sagittal planar human postural balance and biped walking to 1) investigate an explicit mechanism of the cerebrocerebellar and other related neural systems, 2) explain the principles of human postural balancing and biped walking control in terms of the central nervous systems, and 3) provide a biologically inspired framework for the design of humanoid or other biomorphic robot locomotion. The modeling was designed to confirm neurophysiological plausibility and achieve practical simplicity as well. The combination of scheduled long-loop proprioceptive and force feedback represents the cerebrocerebellar system to implement postural balance strategies despite the presence of signal transmission delays and phase lags. The model demonstrates that the postural control can be substantially linear within regions of the kinematic state-space with switching driven by sensed variables.(cont.) A improved and simplified version of the cerebrocerebellar system is combined with the spinal pattern generation to account for human nominal walking and various robustness tasks. The synergy organization of the spinal pattern generation simplifies control of joint actuation. The substantial decoupling of the various neural circuits facilitates generation of modulated behaviors. This thesis suggests that kinematic control with no explicit internal model of body dynamics may be sufficient for those lower body motion tasks and play a common role in postural balance and walking. All simulated performances are evaluated with respect to actual observations of kinematics, electromyogram, etc.by Sungho JoPh.D
Open motion control architecture for humanoid robots
This Ph.D. thesis contributes to the development of control architecture for robots. It provides a complex study of a control systems design and makes a proposal for generalized open motion control architecture for humanoid robots. Generally speaking, the development of humanoid robots is a very complex engineering and scientific task that requires new approaches in mechanical design, electronics, software engineering and control. First of all, taking into account all these considerations, this thesis tries to answer the question of why we need the development of such robots. Further, it provides a study of the evolution of humanoid robots, as well as an analysis of modern trends. A complex study of motion, that for humanoid robots, means first of all the biped locomotion is addressed. Requirements for the design of open motion control architecture are posed. This work stresses the motion control algorithms for humanoid robots. The implementation of only servo control for some types of robots (especially for walking systems) is not sufficient. Even having stable motion pattern and well tuned joint control, a humanoid robot can fall down while walking. Therefore, these robots need the implementation of another, upper control loop which will provide the stabilization of their motion. This Ph.D. thesis proposes the study of a joint motion control problem and a new solution to walking stability problem for humanoids. A new original walking stabilization controller based on decoupled double inverted pendulum dynamical model is developed. This Ph.D. thesis proposes novel motion control software and hardware architecture for humanoid robots. The main advantage of this architecture is that it was designed by an open systems approach allowing the development of high-quality humanoid robotics platforms that are technologically up-to-date. The Rh-1 prototype of the humanoid robot was constructed and used as a test platform for implementing the concepts described in this Ph.D. thesis. Also, the implementation of walking stabilization control algorithms was made with OpenHRP platform and HRP-2 humanoid robot. The simulations and walking experiments showed favourable results not only in forward walking but also in turning and backwards walking gaits. It proved the applicability and reliability of designed open motion control architecture for humanoid robots. Finally, it should be noted that this Ph.D. thesis considers the motion control system of a humanoid robot as a whole, stresses the entire concept-design-implementation chain and develops basic guidelines for the design of open motion control architecture that can be easily implemented in other biped platforms
Towards Robust Bipedal Locomotion:From Simple Models To Full-Body Compliance
Thanks to better actuator technologies and control algorithms, humanoid robots to date can perform a wide range of locomotion activities outside lab environments. These robots face various control challenges like high dimensionality, contact switches during locomotion and a floating-base nature which makes them fall all the time. A rich set of sensory inputs and a high-bandwidth actuation are often needed to ensure fast and effective reactions to unforeseen conditions, e.g., terrain variations, external pushes, slippages, unknown payloads, etc. State of the art technologies today seem to provide such valuable hardware components. However, regarding software, there is plenty of room for improvement. Locomotion planning and control problems are often treated separately in conventional humanoid control algorithms. The control challenges mentioned above are probably the main reason for such separation. Here, planning refers to the process of finding consistent open-loop trajectories, which may take arbitrarily long computations off-line. Control, on the other hand, should be done very fast online to ensure stability. In this thesis, we want to link planning and control problems again and enable for online trajectory modification in a meaningful way. First, we propose a new way of describing robot geometries like molecules which breaks the complexity of conventional models. We use this technique and derive a planning algorithm that is fast enough to be used online for multi-contact motion planning. Similarly, we derive 3LP, a simplified linear three-mass model for bipedal walking, which offers orders of magnitude faster computations than full mechanical models. Next, we focus more on walking and use the 3LP model to formulate online control algorithms based on the foot-stepping strategy. The method is based on model predictive control, however, we also propose a faster controller with time-projection that demonstrates a close performance without numerical optimizations. We also deploy an efficient implementation of inverse dynamics together with advanced sensor fusion and actuator control algorithms to ensure a precise and compliant tracking of the simplified 3LP trajectories. Extensive simulations and hardware experiments on COMAN robot demonstrate effectiveness and strengths of our method. This thesis goes beyond humanoid walking applications. We further use the developed modeling tools to analyze and understand principles of human locomotion. Our 3LP model can describe the exchange of energy between human limbs in walking to some extent. We use this property to propose a metabolic-cost model of human walking which successfully describes trends in various conditions. The intrinsic power of the 3LP model to generate walking gaits in all these conditions makes it a handy solution for walking control and gait analysis, despite being yet a simplified model. To fill the reality gap, finally, we propose a kinematic conversion method that takes 3LP trajectories as input and generates more human-like postures. Using this method, the 3LP model, and the time-projecting controller, we introduce a graphical user interface in the end to simulate periodic and transient human-like walking conditions. We hope to use this combination in future to produce faster and more human-like walking gaits, possibly with more capable humanoid robots
Visual servo control on a humanoid robot
Includes bibliographical referencesThis thesis deals with the control of a humanoid robot based on visual servoing. It seeks to confer a degree of autonomy to the robot in the achievement of tasks such as reaching a desired position, tracking or/and grasping an object. The autonomy of humanoid robots is considered as crucial for the success of the numerous services that this kind of robots can render with their ability to associate dexterity and mobility in structured, unstructured or even hazardous environments. To achieve this objective, a humanoid robot is fully modeled and the control of its locomotion, conditioned by postural balance and gait stability, is studied. The presented approach is formulated to account for all the joints of the biped robot. As a way to conform the reference commands from visual servoing to the discrete locomotion mode of the robot, this study exploits a reactive omnidirectional walking pattern generator and a visual task Jacobian redefined with respect to a floating base on the humanoid robot, instead of the stance foot. The redundancy problem stemming from the high number of degrees of freedom coupled with the omnidirectional mobility of the robot is handled within the task priority framework, allowing thus to achieve con- figuration dependent sub-objectives such as improving the reachability, the manipulability and avoiding joint limits. Beyond a kinematic formulation of visual servoing, this thesis explores a dynamic visual approach and proposes two new visual servoing laws. Lyapunov theory is used first to prove the stability and convergence of the visual closed loop, then to derive a robust adaptive controller for the combined robot-vision dynamics, yielding thus an ultimate uniform bounded solution. Finally, all proposed schemes are validated in simulation and experimentally on the humanoid robot NAO