Robust execution of bipedal walking tasks from biomechanical principles

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 348-352).Effective use of robots in unstructured environments requires that they have sufficient autonomy and agility to execute task-level commands successfully. A challenging example of such a robot is a bipedal walking machine. Such a robot should be able to walk to a particular location within a particular time, while observing foot placement constraints, and avoiding a fall, if this is physically possible. Although stable walking machines have been built, the problem of task-level control, where the tasks have stringent state-space and temporal requirements, and where significant disturbances may occur, has not been studied extensively. This thesis addresses this problem through three objectives. The first is to devise a plan specification where task requirements are expressed in a qualitative form that provides for execution flexibility. The second is to develop a task-level executive that accepts such a plan, and outputs a sequence of control actions that result in successful plan execution. The third is to provide this executive with disturbance handling ability. Development of such an executive is challenging because the biped is highly nonlinear and has limited actuation due to its limited base of support. We address these challenges with three key innovations.(cont.) To address the nonlinearity, we develop a dynamic virtual model controller to linearize the biped, and thus, provide an abstracted biped that is easier to control. The controller is model-based, but uses a sliding control technique to compensate for model inaccuracy. To address the under-actuation, our system generates flow tubes, which define valid operating regions in the abstracted biped. The flow tubes represent sets of state trajectories that take into account dynamic limitations due to under-actuation, and also satisfy plan requirements. The executive keeps trajectories in the flow tubes by adjusting a small number of control parameters for key state variables in the abstracted biped, such as center of mass. Additionally, our system uses a novel strategy that employs angular momentum to enhance translational controllability of the system's center of mass. We evaluate our approach using a high-fidelity biped simulation. Tests include walking with foot-placement constraints, kicking a soccer ball, and disturbance recovery.by Andreas G. Hofmann.Ph.D

Robust Execution of Bipedal Walking Tasks From Biomechanical Principles

PhD thesisEffective use of robots in unstructured environments requires that they have sufficient autonomy and agility to execute task-level commands successfully. A challenging example of such a robot is a bipedal walking machine. Such a robot should be able to walk to a particular location within a particular time, while observing foot placement constraints, and avoiding a fall, if this is physically possible. Although stable walking machines have been built, the problem of task-level control, where the tasks have stringent state-space and temporal requirements, and where significant disturbances may occur, has not been studied extensively. This thesis addresses this problem through three objectives. The first is to devise a plan specification where task requirements are expressed in a qualitative form that provides for execution flexibility. The second is to develop a task-level executive that accepts such a plan, and outputs a sequence of control actions that result in successful plan execution. The third is to provide this executive with disturbance handling ability.Development of such an executive is challenging because the biped is highly nonlinear and has limited actuation due to its limited base of support. We address these challenges with three key innovations. To address the nonlinearity, we develop a dynamic virtual model controller to linearize the biped, and thus, provide an abstracted biped that is easier to control. The controller is model-based, but uses a sliding control technique to compensate for model inaccuracy. To address the under-actuation, our system generates flow tubes, which define valid operating regions in the abstracted biped. The flow tubes represent sets of state trajectories that take into account dynamic limitations due to under-actuation, and also satisfy plan requirements. The executive keeps trajectories in the flow tubes by adjusting a small number of control parameters for key state variables in the abstracted biped, such as center of mass. Additionally, our system uses a novel strategy that employs angular momentum to enhance translational controllability of the systemÂs center of mass. We evaluate our approach using a high-fidelity biped simulation. Tests include walking with foot-placement constraints, kicking a soccer ball, and disturbance recovery

Respiratory, postural and spatio-kinetic motor stabilization, internal models, top-down timed motor coordination and expanded cerebello-cerebral circuitry: a review

Human dexterity, bipedality, and song/speech vocalization in Homo are reviewed within a motor evolution perspective in regard to 

(i) brain expansion in cerebello-cerebral circuitry, 
(ii) enhanced predictive internal modeling of body kinematics, body kinetics and action organization, 
(iii) motor mastery due to prolonged practice, 
(iv) task-determined top-down, and accurately timed feedforward motor adjustment of multiple-body/artifact elements, and 
(v) reduction in automatic preflex/spinal reflex mechanisms that would otherwise restrict such top-down processes. 

Dual-task interference and developmental neuroimaging research argues that such internal modeling based motor capabilities are concomitant with the evolution of 
(vi) enhanced attentional, executive function and other high-level cognitive processes, and that 
(vii) these provide dexterity, bipedality and vocalization with effector nonspecific neural resources. 

The possibility is also raised that such neural resources could 
(viii) underlie human internal model based nonmotor cognitions. 
&#xa

Design and implementation of series elastic actuation in a biomorphic robot leg

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (leaf 21).Fluid, efficient, robust bipedal locomotion is hard by some approaches. Today's most advanced bipedal robots require flat and level floors, but are still prone to trips and falls. They have trouble interacting with objects in their surroundings, and adapting to them. We think that new approaches may make bipedal control easier. The following work details the design of the BOB (Bag of Bones) biomorphic robot leg that is a continuation of an effort to achieve a better understanding of the sensorimotor neurocontrol of locomotion, particularly in humans. Such an understanding will not only lead to robots that move as well or better than people while being easier to control, but will also enable powerful therapies for ataxia patients. One of the main design requirements for BOB was to incorporate series elastic actuation, but with hobby servo motors as the power source. The use of hobby servos was intended to keep costs low, as was the extensive use of off the shelf parts whenever possible. With the recent advances in hobby servo motors, it was expected that reasonable if not high performance would be possible. The specific contribution of this work includes the entire series elastic actuation system powered by servo motors.(Cont.) The elements of the actuation system include circular servo horns, wire rope used in loops, turnbuckles, and series elastic elements that use compression springs in extension. It was found that the knee joint can flex from 0 to 90 degrees and back in about 0.7 seconds. Similarly, the ankle cycled from approximately 20 degrees of extension to approximately 35 degrees of flexion in about 0.7 seconds. These performance figures indicate that the gearing ratios at the knee and ankle are appropriate and that the current design is sufficiently powered for walking.by Nathaniel K. Chan.S.B

Learning Interaction Primitives for Biomechanical Prediction

abstract: This dissertation is focused on developing an algorithm to provide current state estimation and future state predictions for biomechanical human walking features. The goal is to develop a system which is capable of evaluating the current action a subject is taking while walking and then use this to predict the future states of biomechanical features. This work focuses on the exploration and analysis of Interaction Primitives (Amor er al, 2014) and their relevance to biomechanical prediction for human walking. Built on the framework of Probabilistic Movement Primitives, Interaction Primitives utilize an EKF SLAM algorithm to localize and map a distribution over the weights of a set of basis functions. The prediction properties of Bayesian Interaction Primitives were utilized to predict real-time foot forces from a 9 degrees of freedom IMUs mounted to a subjects tibias. This method shows that real-time human biomechanical features can be predicted and have a promising link to real-time controls applications.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion