Hybrid Model for Passive Locomotion Control of a Biped Humanoid:The Artificial Neural Network Approach

Developing a correct model for a biped robot locomotion is extremely challenging due to its inherently unstable structure because of the passive joint located at the unilateral foot-ground contact and varying configurations throughout the gait cycle, resulting variation of dynamic descriptions and control laws from phase to phase. The present research describes the development of a hybrid biped model using an Open Dynamics Engine (ODE) based analytical three link leg model as a base model and, on top of it, an Artificial Neural Network based learning model which ensures better adaptability, better limits cycle behaviors and better generalization while negotiating along a down slope. The base model has been configured according to the individual subjects and data have been collected using a novel technique through an android app from those subjects while walking down a slope. The pattern between the deviation of the actual trajectories and the base model generated trajectories has been found using a back propagation based artificial neural network architecture. It has been observed that this base model with learning based compensation enables the biped to better adapt in a real walking environment, showing better limit cycle behaviors. We also observed the bounded nature of deviation which led us to conclude that the strategy for biped locomotion control is generic in nature and largely dominated by learning

Push Recovery for Humanoid Robot in Dynamic Environment and Classifying the Data Using K-Mean

Push recovery is prime ability that is essential to be incorporated in the process of developing a robust humanoid robot to support bipedalism. In real environment it is very essential for humanoid robot to maintain balance. In this paper we are generating a control system and push recovery controller for humanoid robot walking. We apply different kind of pushes to humanoid robot and the algorithm that can bring a change in the walking stage to sustain walking. The simulation is done in 3D environment using Webots. This paper describes techniques for feature selection to foreshow push recovery for hip, ankle and knee joint. We train the system by K-Mean algorithm and testing is done on crouch data and tested results are reported. Random push data of humanoid robot is collected and classified to see whether push lie in safer region and then tested on given proposed system

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

Control Implementation of Dynamic Locomotion on Compliant, Underactuated, Force-Controlled Legged Robots with Non-Anthropomorphic Design

The control of locomotion on legged robots traditionally involves a robot that takes a standard legged form, such as the anthropomorphic humanoid, the dog-like quadruped, or the bird-like biped. Additionally, these systems will often be actuated with position-controlled servos or series-elastic actuators that are connected through rigid links. This work investigates the control implementation of dynamic, force-controlled locomotion on a family of legged systems that significantly deviate from these classic paradigms by incorporating modern, state-of-the-art proprioceptive actuators on uniquely configured compliant legs that do not closely resemble those found in nature. The results of this work can be used to better inform how to implement controllers on legged systems without stiff, position-controlled actuators, and also provide insight on how intelligently designed mechanical features can potentially simplify the control of complex, nonlinear dynamical systems like legged robots. To this end, this work presents the approach to control for a family of non-anthropomorphic bipedal robotic systems which are developed both in simulation and with physical hardware. The first is the Non-Anthropomorphic Biped, Version 1 (NABi-1) that features position-controlled joints along with a compliant foot element on a minimally actuated leg, and is controlled using simple open-loop trajectories based on the Zero Moment Point. The second system is the second version of the non-anthropomorphic biped (NABi-2) which utilizes the proprioceptive Back-drivable Electromagnetic Actuator for Robotics (BEAR) modules for actuation and fully realizes feedback-based force controlled locomotion. These systems are used to highlight both the strengths and weaknesses of utilizing proprioceptive actuation in systems, and suggest the tradeoffs that are made when using force control for dynamic locomotion. These systems also present case studies for different approaches to system design when it comes to bipedal legged robots

What is Robotics: Why Do We Need It and How Can We Get It?

Robotics is an emerging synthetic science concerned with programming work. Robot technologies are quickly advancing beyond the insights of the existing science. More secure intellectual foundations will be required to achieve better, more reliable and safer capabilities as their penetration into society deepens. Presently missing foundations include the identification of fundamental physical limits, the development of new dynamical systems theory and the invention of physically grounded programming languages. The new discipline needs a departmental home in the universities which it can justify both intellectually and by its capacity to attract new diverse populations inspired by the age old human fascination with robots. For more information: Kod*la

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

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

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