Browsing by Author "Saranli, U."

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Open Access
Efficient bipedal locomotion on rough terrain via compliant ankle actuation with energy regulation
(Institute of Physics Publishing Ltd., 2021-08-12) Kerimoğlu, Deniz; Karkoub, M.; Uyanik, I.; Morgül, Ömer; Saranli, U.
Legged locomotion enables robotic platforms to traverse on rough terrain, which is quite challenging for other locomotion types, such as in wheeled and tracked systems. However, this benefit—moving robustly on rough terrain—comes with an inherent drawback due to the higher cost of transport in legged robots. The ultimate need for energy efficiency motivated the utilization of passive dynamics in legged locomotion. Nevertheless, a handicap in passive dynamic walking is the fragile basin of attraction that limits the locomotion capabilities of such systems. There have been various extensions to overcome such limitations by incorporating additional actuators and active control approaches at the expense of compromising the benefits of passivity. Here, we present a novel actuation and control framework, enabling efficient and sustained bipedal locomotion on significantly rough terrain. The proposed approach reinforces the passive dynamics by intermittent active feedback control within a bio-inspired compliant ankle actuation framework. Specifically, we use once-per-step energy regulation to adjust the spring precompression of the compliant ankle based on the liftoff instants—when the toe liftoffs from the ground—of the locomotion. Our results show that the proposed approach achieves highly efficient (with a cost of transport of 0.086) sustained locomotion on rough terrain, withstanding height variations up to 15% of the leg length. We provide theoretical and numerical analysis to demonstrate the performance of our approach, including systematic comparisons with the recent and state-of-the-art techniques in the literature.
Open Access
Experimental validation of a feed-forward predictor for the spring-loaded inverted pendulum template
(IEEE, 2015-02) Uyanik, I.; Morgül, O.; Saranli, U.
Widely accepted utility of simple spring-mass models for running behaviors as descriptive tools, as well as literal control targets, motivates accurate analytical approximations to their dynamics. Despite the availability of a number of such analytical predictors in the literature, their validation has mostly been done in simulation, and it is yet unclear how well they perform when applied to physical platforms. In this paper, we extend on one of the most recent approximations in the literature to ensure its accuracy and applicability to a physical monopedal platform. To this end, we present systematic experiments on a well-instrumented planar monopod robot, first to perform careful identification of system parameters and subsequently to assess predictor performance. Our results show that the approximate solutions to the spring-loaded inverted pendulum dynamics are capable of predicting physical robot position and velocity trajectories with average prediction errors of 2% and 7%, respectively. This predictive performance together with the simple analytic nature of the approximations shows their suitability as a basis for both state estimators and locomotion controllers. © 2004-2012 IEEE.
Open Access
Frequency-domain subspace ıdentification of linear time periodic (LTP) systems
(Institute of Electrical and Electronics Engineers, 2019) Uyanik, I.; Saranli, U.; Ankaralı, M.; Cowan, N. J.; Morgül, Ömer
This note proposes a new methodology for subspace-based state-space identification for linear time-periodic (LTP) systems. Since LTP systems can be lifted to equivalent linear time-invariant (LTI) systems, we first lift input-output data from the unknown LTP system as if it was collected from an equivalent LTI system. Then, we use frequency-domain subspace identification methods to find an LTI system estimate. Subsequently, we propose a novel method to obtain a time-periodic realization for the estimated lifted LTI system by exploiting the specific parametric structure of Fourier series coefficients of the frequency-domain lifting method. Our method can be used to both obtain state-space estimates for unknown LTP systems as well as to obtain Floquet transforms for known LTP systems. IEEE
Open Access
LinGraph: a graph-based automated planner for concurrent task planning based on linear logic
(Springer New York LLC, 2017) Kortik S.; Saranli, U.
In this paper, we introduce an automated planner for deterministic, concurrent domains, formulated as a graph-based theorem prover for a propositional fragment of intuitionistic linear logic, relying on the previously established connection between intuitionistic linear logic and planning problems. The new graph-based theorem prover we introduce improves planning performance by reducing proof permutations that are irrelevant to planning problems particularly in the presence of large numbers of objects and agents with identical properties (e.g. robots within a swarm, or parts in a large factory). We first present our graph-based automated planner, the Linear Logic Graph Planner (LinGraph). Subsequently we illustrate its application for planning within a concurrent manufacturing domain and provide comparisons with four existing automated planners, BlackBox, Symba-2, Metis and the Temporal Fast Downward (TFD), covering a wide range of state-of-the-art automated planning techniques and implementations. We show that even though LinGraph does not rely on any heuristics, it still outperforms these systems for concurrent domains with large numbers of identical objects and agents. These gains persist even when existing methods on symmetry reduction and numerical fluents are used, with LinGraph capable of handling problems with thousands of objects. Following these results, we also show that plan construction with LinGraph is equivalent to multiset rewriting systems, formally relating LinGraph to intuitionistic linear logic. © 2017, Springer Science+Business Media New York.
Open Access
Stability and control of planar compass gait walking with series-elastic ankle actuation
(Sage Publications Ltd., 2017) Kerimoğlu, D.; Morgül, Ö.; Saranli, U.
Passive dynamic walking models are capable of capturing basic properties of walking behaviours and can generate stable human-like walking without any actuation on inclined surfaces. The passive compass gait model is among the simplest of such models, consisting of a planar point mass and two stick legs. A number of different actuation methods have been proposed both for this model and its more complex extensions to eliminate the need for a sloped ground, balancing collision losses using gravitational potential energy. In this study, we introduce and investigate an extended model with serieselastic actuation at the ankle towards a similar goal, realizing stable walking on level ground. Our model seeks to capture the basic structure of how humans utilize toe push-off prior to leg liftoff, and is intended to eventually be used for controlling the ankle joint in a lower-body robotic orthosis. We derive hybrid equations of motion for this model, and show numerically through Poincare´ analysis that it can achieve asymptotically stable walking on level ground for certain choices of system parameters. We then study the bifurcation regimes of period doubling with this model, leading up to chaotic walking patterns. Finally, we show that feedback control on the initial extension of the series ankle spring can be used to improve and extend system stability.
Open Access
Stride-to-stride energy regulation for robust self-stability of a torque-actuated dissipative spring-mass hopper
(A I P Publishing LLC, 2010) Ankarali, M. M.; Saranli, U.
In this paper, we analyze the self-stability properties of planar running with a dissipative spring-mass model driven by torque actuation at the hip. We first show that a two-dimensional, approximate analytic return map for uncontrolled locomotion with this system under a fixed touchdown leg angle policy and an open-loop ramp torque profile exhibits only marginal self-stability that does not always persist for the exact system. We then propose a per-stride feedback strategy for the hip torque that explicitly compensates for damping losses, reducing the return map to a single dimension and substantially improving the robust stability of fixed points. Subsequent presentation of simulation evidence establishes that the predictions of this approximate model are consistent with the behavior of the exact plant model. We illustrate the relevance and utility of our model both through the qualitative correspondence of its predictions to biological data as well as its use in the design of a task-level running controller. © 2010 American Institute of Physics.