Energetics of an Inertia Coupled and Simple Rimless Wheel

It has been shown by others that it is theoretically possible for a walking robot to achieve a perfectly efficient gait. The simplest model capable of highly efficient walking motions is the Inertial Coupled Rimless (ICR) Wheel. To examine the dynamics of the ICR wheel, two related studies were done. To determine the lowest energy cost for the ICR wheel we examined one mechanism of energy loss, non-elastic deformation of the elastic elements. Quasi-static experimental tension tests determined that the minimal energy loss for our system was 8:4x10�4 Joules per cycle. A more realistic, high frequency test, showed that the energy loss increased by a factor of 9.16. The ICR wheel walks down a ramp which is assumed to be very at. But no surface in reality can be perfectly at. For a more realistic study, rough terrain is introduced to the ramp. To better understand the dynamics of the motion of the ICR wheel, a simple rimless (SR) wheel is examined on a ramp with roughness. The roughness of the ground is randomly generated but bounded in magnitude. The minimum angle of inclination required for a rimless wheel to walk down both smooth and rough ramps is determined. For the rimless wheel we examined with 5 legs, the minimum slope required for a rough surface is 12.4% higher than that required for a smooth surface, and for 10 legs, the minimum slope for a rough surface is 40.83% higher than the smooth surface. This work has formed the foundation for the design of an energy efficient walking robot and has given insight into its behavior over rough terrain

Dynamics of the Inertia Coupled Rimless Wheel with Frictional Losses and Actuation

The Inertia Coupled Rimless (ICR) wheel is a mechanically simple walking device capable of energy efficient motion. Typically, walking robots that are capable of level ground transport are extremely energy inefficient. To address this performance issue, the ICR wheel was examined while considering real-world frictional losses. The ICR wheel has been previously shown to be capable of collisionless, periodic motion, but until now, the ICR wheel had only been examined as an ideal, theoretical model. The inertia device within the system was tested to determine both the magnitude of energy loss due to damping and a suitable model for its motion. Fitting friction models to the experimental results showed that the a visciously damped model most accurately represented the system\u27s motion. Simulations revealed that the ICR wheel with friction would be capable of walking passively on a ramp with half stable, periodic walking, but the collisionless motion was lost. An actuation scheme was designed in simulation to allow an ICR wheel with damping to achieve collisionless motion on level ground. Experimental testing of a passive ICR wheel on a $3^o$ ramp showed that a cost of transport of at least 0.052 is possible with this system. Simulations suggest that, with the inclusion of an actuation scheme, the cost of transport for the same system on level ground could be as low as 0.024. Understanding how to overcome frictional losses lays the foundation for the creation of a walking robot capable of level ground transport with significantly less energy use than current models are capable of achieving

A Rule Based Biped Dynamic Walking

Dynamic walking approach has got its significance because of its energy efficiency in walking. Walking models are made using this approach which would consume energy as low as the energy required for human being walking. The basis of this dynamic walking is purely passive walking which takes no energy for walking. For a simple compass model passive walking can be achieved only for particular initial conditions (angular positions and velocities) which are found by trial and error or from previous experience.Various ways are derived to make the model walk on a level ground by supplying external energy through some means i.e torques at hip joint and ankle joints which is called active walking. Two approaches are available for active walking, one is creating virtual slope and then by applying equivalent torques at ankle and hip as the functions of virtual slope;other approach is using torsional springs and dampers at hip as well as ankles such that the torques are given in terms of springs' stiffness coefficient and damping coefficient. The stability is analyzed based on ZMP position. When ZMP of the system falls within the foot support area then system is said to be stable

Optimization-based Framework for Stability and Robustness of Bipedal Walking Robots

As robots become more sophisticated and move out of the laboratory, they need to be able to reliably traverse difficult and rugged environments. Legged robots -- as inspired by nature -- are most suitable for navigating through terrain too rough or irregular for wheels. However, control design and stability analysis is inherently difficult since their dynamics are highly nonlinear, hybrid (mixing continuous dynamics with discrete impact events), and the target motion is a limit cycle (or more complex trajectory), rather than an equilibrium. For such walkers, stability and robustness analysis of even stable walking on flat ground is difficult. This thesis proposes new theoretical methods to analyse the stability and robustness of periodic walking motions. The methods are implemented as a series of pointwise linear matrix inequalities (LMI), enabling the use of convex optimization tools such as sum-of-squares programming in verifying the stability and robustness of the walker. To ensure computational tractability of the resulting optimization program, construction of a novel reduced coordinate system is proposed and implemented. To validate theoretic and algorithmic developments in this thesis, a custom-built “Compass gait” walking robot is used to demonstrate the efficacy of the proposed methods. The hardware setup, system identification and walking controller are discussed. Using the proposed analysis tools, the stability property of the hardware walker was successfully verified, which corroborated with the computational results

Metastable legged-robot locomotion

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.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. 195-215).A variety of impressive approaches to legged locomotion exist; however, the science of legged robotics is still far from demonstrating a solution which performs with a level of flexibility, reliability and careful foot placement that would enable practical locomotion on the variety of rough and intermittent terrain humans negotiate with ease on a regular basis. In this thesis, we strive toward this particular goal by developing a methodology for designing control algorithms for moving a legged robot across such terrain in a qualitatively satisfying manner, without falling down very often. We feel the definition of a meaningful metric for legged locomotion is a useful goal in and of itself. Specifically, the mean first-passage time (MFPT), also called the mean time to failure (MTTF), is an intuitively practical cost function to optimize for a legged robot, and we present the reader with a systematic, mathematical process for obtaining estimates of this MFPT metric. Of particular significance, our models of walking on stochastically rough terrain generally result in dynamics with a fast mixing time, where initial conditions are largely "forgotten" within 1 to 3 steps. Additionally, we can often find a near-optimal solution for motion planning using only a short time-horizon look-ahead. Although we openly recognize that there are important classes of optimization problems for which long-term planning is required to avoid "running into a dead end" (or off of a cliff!), we demonstrate that many classes of rough terrain can in fact be successfully negotiated with a surprisingly high level of long-term reliability by selecting the short-sighted motion with the greatest probability of success. The methods used throughout have direct relevance to machine learning, providing a physics-based approach to reduce state space dimensionality and mathematical tools to obtain a scalar metric quantifying performance of the resulting reduced-order system.by Katie Byl.Ph.D

On the discretisation of actuation in locomotion: Impulse- and shape-based modelling for hopping robots

In an age where computers challenge the smartest human beings in cognitive tasks, the conspicuous discrepancy between robot and animal locomotion appears paradoxical. While animals can move around autonomously in complex environments, today’s robots struggle to independently operate in such surroundings. There are many reasons for robots’ inferior performance, but arguably the most important one is our missing understanding of complexity. This thesis introduces the notion of discrete actuation for the study of locomotion in robots and animals. The actuation of a system with discrete actuation is restricted to be applied at a finite number of instants in time and is impulsive. We find that, despite their simplicity, such systems can predict various experimental observations and inspire novel technologies for robot design and control. We further find that, through the study of discrete actuation, causal relationships between actuation and resulting behaviour are revealed and become quantifiable, which relates the findings presented in this thesis to the broader concepts of complexity, self-organisation, and self-stability. We present four case studies in Chapters 3-6 which demonstrate how the concept of discrete actuation can be employed to understand the physics of locomotion and to facilitate novel robot technologies. We first introduce the impulsive eccentric wheel model which is a discretely actuated system for the study of hopping locomotion. We find that the model predicts robot hopping trajectories and animal related hopping characteristics by reducing the dynamics of hopping–usually described by hybrid differential equations–to analytic maps. The reduction of complexity of the model equations reveals the underlying physics of the locomotion process, and we identify the importance of robot shape and mass distribution for the locomotion performance. As a concrete application of the model, we compare the energetics of hopping and rolling locomotion in environments with obstacles and find when it is better to hop than to roll, based on the fundamental physical principles we discover in the model analysis. The theoretical insights of this modelling approach enable new actuation techniques and design for robots which we display in Robbit; a robot that uses strictly convex foot shapes and rotational impulses to induce hopping locomotion. We show that such systems outperform hopping with non-strictly convex shapes in terms of energy effective and robust locomotion. A system with discrete actuation motivates the exploitation of shape and the environment to improve locomotion dynamics, which reveals advantageous effect of inelastic impacts between the robot foot and the environment. We support this idea with experimental results from the robot CaneBot which can change its foot shape to induce timed impacts with the environment. Even though inelastic impacts are commonly considered detrimental for locomotion dynamics, we show that their appropriate control improves the locomotion speed considerably. The findings presented in this thesis show that discrete actuation for locomotion inspires novel ways to appreciate locomotion dynamics and facilitates unique control and design technologies for robots. Furthermore, discrete actuation emphasises the definition of causality in complex systems which we believe will bring robots closer to the locomotion behaviour of animals, enabling more agile and energy effective robots

Towards energy-efficient limit-cycle walking in biped service robots: design analysis, modeling and experimental study of biped robot actuated by linear motors

Researchers have been studying biped robots for many years, and, while many advances in the field have been accomplished, there still remain the challenge to transfer the existing solutions into real applications. The main issues are related to mobility and autonomy. In mobility, biped robots have evolved greatly, nevertheless they are still far from what a human can do in the work-site. Similarly, autonomy of biped platforms has been tackled on several different grounds, but its core problem still remains, and it is associated to energy issues. Because of these energy issues, lately the main attention has been redirected to the long term autonomy of the biped robotics platforms. For that, much effort has been made to develop new more energy-efficient biped robots. The GIMBiped project in Aalto University was established to tackle the previous issues in energy efficiency and mobility, through the study and implementation of dynamic and energy-efficient bipedal robotic waking. This thesis falls into the first studies needed to achieve the previous goal using the GIMBiped testbed, starting with a detailed analysis of the nonlinear dynamics of the target system, using a modeling and simulation tools. This work also presents an assessment of different control techniques based on Limit Cycle walking, carried out on a two-dimensional kneed bipedal simulator. Furthermore, a numerical continuation analysis of the mechanical parameters of the first GIMBiped prototype was performed, using the same approximated planar kneed biped model. This study is done to analyze the effect that such variations in the mechanical design parameters produce in the stability and energy-efficiency of the system.Finally, experiments were performed in the GIMBiped testbed. These experiments show the results of a hybrid control technique proposed by the author, which combines traditional ZMP-based walking approach with a Limit Cycle trajectory-following control. Furthermore the results of a pure ZMP-based type of control are also presented.

Sand and Dust on Mars

Mars is a planet of high scientific interest. Various studies are currently being made that involve vehicles that have landed on Mars. Because Mars is known to experience frequent wind storms, mission planners and engineers require knowledge of the physical and chemical properties of Martian windblown sand and dust, and the processes involved in the origin and evolution of sand and dust storms

System Identification of Bipedal Locomotion in Robots and Humans

The ability to perform a healthy walking gait can be altered in numerous cases due to gait disorder related pathologies. The latter could lead to partial or complete mobility loss, which affects the patients’ quality of life. Wearable exoskeletons and active prosthetics have been considered as a key component to remedy this mobility loss. The control of such devices knows numerous challenges that are yet to be addressed. As opposed to fixed trajectories control, real-time adaptive reference generation control is likely to provide the wearer with more intent control over the powered device. We propose a novel gait pattern generator for the control of such devices, taking advantage of the inter-joint coordination in the human gait. Our proposed method puts the user in the control loop as it maps the motion of healthy limbs to that of the affected one. To design such control strategy, it is critical to understand the dynamics behind bipedal walking. We begin by studying the simple compass gait walker. We examine the well-known Virtual Constraints method of controlling bipedal robots in the image of the compass gait. In addition, we provide both the mechanical and control design of an affordable research platform for bipedal dynamic walking. We then extend the concept of virtual constraints to human locomotion, where we investigate the accuracy of predicting lower limb joints angular position and velocity from the motion of the other limbs. Data from nine healthy subjects performing specific locomotion tasks were collected and are made available online. A successful prediction of the hip, knee, and ankle joints was achieved in different scenarios. It was also found that the motion of the cane alone has sufficient information to help predict good trajectories for the lower limb in stairs ascent. Better estimates were obtained using additional information from arm joints. We also explored the prediction of knee and ankle trajectories from the motion of the hip joints