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36
Issues in Evolutionary Robotics
, 1992
"... In this paper we propose and justify a methodology for the development of the control systems, or `cognitive architectures', of autonomous mobile robots. We argue that the design by hand of such control systems becomes prohibitively difficult as complexity increases. We discuss an alternative a ..."
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Cited by 272 (33 self)
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In this paper we propose and justify a methodology for the development of the control systems, or `cognitive architectures', of autonomous mobile robots. We argue that the design by hand of such control systems becomes prohibitively difficult as complexity increases. We discuss an alternative approach, involving artificial evolution, where the basic building blocks for cognitive architectures are adaptive noise-tolerant dynamical neural networks, rather than programs. These networks may be recurrent, and should operate in real time. Evolution should be incremental, using an extended and modified version of genetic algorithms. We nally propose that, sooner rather than later, visual processing will be required in order for robots to engage in non-trivial navigation behaviours. Time constraints suggest that initial architecture evaluations should be largely done in simulation. The pitfalls of simulations compared with reality are discussed, together with the importance of incorporating noise. To support our claims and proposals, we present results from some preliminary experiments where robots which roam office-like environments are evolved.
A Compliant Hybrid Zero Dynamics Controller for Stable, Efficient and Fast Bipedal Walking on MABEL
"... The planar bipedal testbed MABEL contains springs in its drivetrain for the purpose of enhancing both energy efficiency and agility of dynamic locomotion. While the potential energetic benefits of springs are well documented in the literature, feedback control designs that effectively realize this ..."
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Cited by 44 (22 self)
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The planar bipedal testbed MABEL contains springs in its drivetrain for the purpose of enhancing both energy efficiency and agility of dynamic locomotion. While the potential energetic benefits of springs are well documented in the literature, feedback control designs that effectively realize this potential are lacking. In this paper, we extend and apply the methods of virtual constraints and hybrid zero dynamics, originally developed for rigid robots with a single degree of underactuation, to MABEL, a bipedal walker with a novel compliant transmission and multiple degrees of underactuation. A time-invariant feedback controller is designed such that the closed-loop system respects the natural compliance of the open-loop system and realizes exponentially stable walking gaits. Five experiments are presented that highlight different aspects of MABEL and the feedback design method, ranging from basic elements such as stable walking and robustness under perturbations, to energy efficiency and a bipedal robot walking speed record of1.5 m/s (3.4 mph). The experiments also compare two feedback implementations of the virtual constraints, one based on PD control as in [1], and a second that implements the full hybrid zero dynamics controller. On MABEL, the full hybrid zero dynamics controller yields a much more faithful realization of the desired virtual constraints and was instrumental in achieving more rapid walking.
Limit Cycle Walking
- In Hackel, M., Ed., Humanoid Robots: Human-Like Machines, Itech
, 2007
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2008b). Controlling the walking speed in limit cycle walking
- The International Journal of Robotics Research
"... “Limit Cycle Walking ” is a relatively new paradigm for the design and control of two-legged walking robots. It states that achieving sta-ble periodic gait is possible without locally stabilizing the walking trajectory at every instant in time, as is traditionally done in most walking robots. Well-k ..."
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Cited by 6 (0 self)
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“Limit Cycle Walking ” is a relatively new paradigm for the design and control of two-legged walking robots. It states that achieving sta-ble periodic gait is possible without locally stabilizing the walking trajectory at every instant in time, as is traditionally done in most walking robots. Well-known examples of Limit Cycle Walkers are the Passive Dynamic Walkers, but recently there are also many actuated Limit Cycle Walkers. Limit Cycle Walkers generally use less energy than other existing bipeds, but thus far they have not been as ver-satile. This paper focuses on one aspect of versatility: walking speed. We study how walking speed can be varied, which way is energetically beneficial and how walking speed affects a walker’s ability to handle disturbances (that is, disturbance rejection). The study is performed using one prototype and one simulation model. The speed of these two walkers is adapted by changing three parameters: the amount of
The RunBot Architecture for Adaptive, Fast, Dynamic Walking
"... In this paper we will present the architecture of the planar biped robot “RunBot”. It has been developed on the basis of three hierarchical levels: Biomechanical, Local and Central. The biomechanical level concerns an appropriate biomechanical design of RunBot which utilizes some principles of pass ..."
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Cited by 5 (0 self)
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In this paper we will present the architecture of the planar biped robot “RunBot”. It has been developed on the basis of three hierarchical levels: Biomechanical, Local and Central. The biomechanical level concerns an appropriate biomechanical design of RunBot which utilizes some principles of passive walkers to ensure stability. The local level is a lowlevel neuronal structure which generates dynamically stable gaits as well as fast motions with some degree of self-stabilization to guarantee basic robustness. In the central level, we simulate a mechanism for synaptic plasticity which allows RunBot to autonomously learn to adapt its locomotion to different terrains, e.g. level floor versus up or down a ramp. As a result, the structural coupling of all these levels generates adaptive, fast dynamic walking of RunBot.
Feedback Control of a Bipedal Walker and Runner with Compliance
, 2011
"... ii ACKNOWLEDGEMENTS Well, I’m finally writing the acknowledgments. I would like to thank my advisor, Prof. Jessy Grizzle, for creating a wonderful opportunity for me to work on legged locomotion, for his dedication in nurturing me, for his patience and enthusiasm, for his fabulous intellectual suppo ..."
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Cited by 4 (2 self)
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ii ACKNOWLEDGEMENTS Well, I’m finally writing the acknowledgments. I would like to thank my advisor, Prof. Jessy Grizzle, for creating a wonderful opportunity for me to work on legged locomotion, for his dedication in nurturing me, for his patience and enthusiasm, for his fabulous intellectual support, and for giving me the freedom to explore ideas. I would like to thank my dissertation committee members, Prof. Anthony Bloch, Prof. Arthur Kuo, Prof. Harris McClamroch, and Prof. Semyon Meerkov, for their help and support. I would like to thank Hae-Won Park for his many roles as collaborator, co-author, travel companion, and friend throughout my years at the university. I would like to thank Ben Morris for his role as a fantastic mentor during my early years, for his many theoretical contributions that I routinely employ to make my work easier, and for his excellent advice- “Go big, or go home, ” which helped get the running experiments rolling. I would like to thank Ioannis Poulakakis for providing inspiration, for creating the framework of compliant hybrid zero dynamics that I happily borrowed, for solving many of my technical difficulties, and for providing great help as I looked for a job. I would like to thank Jonathan Hurst for creating MABEL, which enabled this
An experimental comparison of bayesian optimization for bipedal locomotion
- In Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA
, 2014
"... Abstract — The design of gaits and corresponding control policies for bipedal walkers is a key challenge in robot loco-motion. Even when a viable controller parametrization already exists, finding near-optimal parameters can be daunting. The use of automatic gait optimization methods greatly reduces ..."
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Cited by 4 (2 self)
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Abstract — The design of gaits and corresponding control policies for bipedal walkers is a key challenge in robot loco-motion. Even when a viable controller parametrization already exists, finding near-optimal parameters can be daunting. The use of automatic gait optimization methods greatly reduces the need for human expertise and time-consuming design processes. Many different approaches to automatic gait optimization have been suggested to date. However, no extensive comparison among them has yet been performed. In this paper, we present some common methods for automatic gait optimization in bipedal locomotion, and analyze their strengths and weaknesses. We experimentally evaluated these gait optimization methods on a bipedal robot, in more than 1800 experimental evaluations. In particular, we analyzed Bayesian optimization in different configurations, including various acquisition functions. I.
Compliant Ankles and Flat Feet for Improved Self-Stabilization and Passive Dynamics of the Biped Robot “RunBot”
"... Abstract—Biomechanical studies of human walking reveal that compliance plays an important role at least in natural and smooth motions as well as for self-stabilization. Inspired by this, we present here the development of a new lower leg segment of the dynamic biped robot “RunBot”. This new lower le ..."
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Abstract—Biomechanical studies of human walking reveal that compliance plays an important role at least in natural and smooth motions as well as for self-stabilization. Inspired by this, we present here the development of a new lower leg segment of the dynamic biped robot “RunBot”. This new lower leg segment features a compliant ankle connected to a flat foot. It is mainly employed to realize robust self-stabilization in a passive manner. In general, such self-stabilization is achieved through mechanical feedback due to elasticity. Using real-time walking experiments, this study shows that the new lower leg segment improves dynamic walking behavior of the robot in two main respects compared to an old lower leg segment consisting of rigid ankle and curved foot: 1) it provides better self-stabilization after stumbling and 2) it increases passive dynamics during some stages of the gait cycle of the robot; i.e., when the whole robot moves unactuated. As a consequence, a combination of compliance (i.e., the new lower leg segment) and active components (i.e., actuated hip and knee joints) driven by a neural mechanism (i.e., reflexive neural control) enables RunBot to perform robust self-stabilization and at the same time natural, smooth, and energy-efficient walking behavior without high control effort. I.
