Optimal and robust walking using intrinsic properties of a series-elastic robot

Werner, A.; Henze, Bernd; Loeffl, Florian; Leyendecker, Sigrid; Ott, Christian

doi:10.1109/humanoids.2017.8239549

Cited by 7 publications

(10 citation statements)

References 19 publications

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“…Reasoning over higher order terms results in solutions with a higher degree of continuity, which improves performance on hardware considerably. This can be achieved by selecting a smooth parameterization of the solution space as done in spline based optimization [15], [16], [17], collocation methods [18], [19], or when using dynamic motion primitives [20]. This, however, limits the motions that can be expressed and can often require a problem-specific, manual tuning procedure.…”

Section: A Related Workmentioning

confidence: 99%

Frequency-Aware Model Predictive Control

Grandia

Farshidian

Dosovitskiy

et al. 2019

IEEE Robot. Autom. Lett.

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Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic tasks, the presence of unmodeled dynamics renders the motion infeasible on the real system. Model errors can be a result of model simplifications, but also naturally arise when deploying the robot in unstructured and nondeterministic environments. Predominantly, compliant contacts and actuator dynamics lead to bandwidth limitations. While classical control methods provide tools to synthesize controllers that are robust to a class of model errors, such a notion is missing in modern trajectory optimization, which is solved in the time domain. We propose frequency-shaped cost functions to achieve robust solutions in the context of optimal control for legged robots. Through simulation and hardware experiments we show that motion plans can be made compatible with bandwidth limits set by actuators and contact dynamics. The smoothness of the model predictive solutions can be continuously tuned without compromising the feasibility of the problem. Experiments with the quadrupedal robot ANYmal, which is driven by highlycompliant series elastic actuators, showed significantly improved tracking performance of the planned motion, torque, and force trajectories and enabled the machine to walk robustly on terrain with unmodeled compliance.

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Section: A Related Workmentioning

confidence: 99%

Frequency-Aware Model Predictive Control

Grandia

Farshidian

Dosovitskiy

et al. 2019

IEEE Robot. Autom. Lett.

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“…Building on the open-source software and hardware mentioned earlier, such control approaches could contribute to the development of cheaper, more robust and versatile robots, which looks like the next logical step now that legged locomotion is being demonstrated robustly in generic indoor and outdoor environments and approaching real industrial scenarios [99,100]. Deformable elements could also contribute to this objective [101].…”

Section: Discussionmentioning

confidence: 99%

Recent Progress in Legged Robots Locomotion Control

Carpentier

Wieber

2021

Curr Robot Rep

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Purpose of review In recent years, legged robots locomotion has been transitioning from mostly flat ground in controlled settings to generic indoor and outdoor environments, approaching now real industrial scenarios. This paper aims at documenting some of the key progress made in legged locomotion control that enabled this transition.Recent findings Legged locomotion control makes extensive use of numerical trajectory optimization and its online implementation, model predictive control. A key progress has been how this optimization is handled, with refined models and refined numerical methods. This led the legged locomotion research community to heavily invest in and contribute to the development of new optimization methods and efficient numerical software. SummaryWe present an overview of the typical approach to legged locomotion control, which involves primarily planning a sequence of contacts with the environment and computing a corresponding dynamically feasible trajectory of the Center of Mass of the robot. We then detail recent progress in contact planning and trajectory optimization with either the full Lagrangian dynamics of legged robots or with reduced models.

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“…where I p is the pxp identity matrix. Equation (7) can then be reformulated using ( 9) and (10) to obtain A 1 , B 1,u , and B 1,F for p joints:…”

Section: Modeling a Actuator Dynamicsmentioning

confidence: 99%

“…Spline-parameterized, nonlinear programming (NLP) and collocation approaches, based on general purpose large-scale NLP libraries, have been successfully applied to series elastic robots. In [10], optimal walking trajectories are produced via NLP to be consistent with compliant dynamics subject to all relevant constraints with pre-defined contact transition times. [11] adds a collocation method to automatically select contacts, to automatically generate multiple steps of walking, and to jump, at the cost of approximating some actuator constraints.…”

Section: Introductionmentioning

confidence: 99%

Exploiting the Natural Dynamics of Series Elastic Robots by Actuator-Centered Sequential Linear Programming

Schlossman

Thomas

Campbell

et al. 2018

2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Series elastic robots are best able to follow trajectories which obey the limitations of their actuators, since they cannot instantly change their joint forces. In fact, the performance of series elastic actuators can surpass that of ideal force source actuators by storing and releasing energy. In this paper, we formulate the trajectory optimization problem for series elastic robots in a novel way based on sequential linear programming. Our framework is unique in the separation of the actuator dynamics from the rest of the dynamics, and in the use of a tunable pseudo-mass parameter that improves the discretization accuracy of our approach. The actuator dynamics are truly linear, which allows them to be excluded from trust-region mechanics. This causes our algorithm to have similar run times with and without the actuator dynamics. We demonstrate our optimization algorithm by tuning high performance behaviors for a single-leg robot in simulation and on hardware for a single degree-of-freedom actuator testbed. The results show that compliance allows for faster motions and takes a similar amount of computation time.

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Optimal and robust walking using intrinsic properties of a series-elastic robot

Cited by 7 publications

References 19 publications

Frequency-Aware Model Predictive Control

Frequency-Aware Model Predictive Control

Recent Progress in Legged Robots Locomotion Control

Exploiting the Natural Dynamics of Series Elastic Robots by Actuator-Centered Sequential Linear Programming

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