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Journal ArticleDOI

Flexible muscle-based locomotion for bipedal creatures

TLDR
A muscle-based control method for simulated bipeds in which both the muscle routing and control parameters are optimized yields a generic locomotion control method that supports a variety of bipedal creatures.
Abstract
We present a muscle-based control method for simulated bipeds in which both the muscle routing and control parameters are optimized. This yields a generic locomotion control method that supports a variety of bipedal creatures. All actuation forces are the result of 3D simulated muscles, and a model of neural delay is included for all feedback paths. As a result, our controllers generate torque patterns that incorporate biomechanical constraints. The synthesized controllers find different gaits based on target speed, can cope with uneven terrain and external perturbations, and can steer to target directions.

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Citations
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Journal ArticleDOI

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills

TL;DR: In this paper, the authors use reinforcement learning to learn robust control policies capable of imitating a broad range of example motion clips, while also learning complex recoveries, adapting to changes in morphology, and accomplishing user-specified goals.
Journal ArticleDOI

Evolutionary Robotics: What, Why, and Where to

TL;DR: The main achievements of evolutionary robotics are considered, focusing particularly on its contributions to both engineering and biology, and some of the most interesting findings are reviewed.
Journal ArticleDOI

Design of the Hydraulically Actuated, Torque-Controlled Quadruped Robot HyQ2Max

TL;DR: In this paper, the authors presented the design of the hydraulically actuated quadruped robot HyQ2Max, which is an evolution of the 80 kg agile and versatile robot HQ. Compared to HQ, the new robot needs to be more rugged, more powerful and extend the existing locomotion skills with self-righting capability.
Journal ArticleDOI

Inverse Kinematics Techniques in Computer Graphics: A Survey

TL;DR: This survey presents a comprehensive review of the IK problem and the solutions developed over the years from the computer graphics point of view, and suggests which IK family of solvers is best suited for particular problems.
Journal ArticleDOI

SFV: reinforcement learning of physical skills from videos

TL;DR: In this article, a method that enables physically simulated characters to learn skills from videos (SFV) is proposed, based on deep pose estimation and deep reinforcement learning, allowing data-driven animation to leverage the abundance of publicly available video clips from the web.
References
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Journal Article

Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control

TL;DR: Their integrated ability to generate force statically and dynamically is studied by formulating a generic model of the "musculotendon actuator", which has only one parameter, the ratio of tendon length at rest to muscle fiberlength at rest.
Book ChapterDOI

The CMA Evolution Strategy: A Comparing Review

TL;DR: In this review, the argument starts out with large population sizes, reflecting recent extensions of the CMA algorithm, and similarities and differences to continuous Estimation of Distribution Algorithms are analyzed.
Journal ArticleDOI

Dynamic optimization of human walking.

TL;DR: The simulation results suggest that minimum metabolic energy per unit distance traveled is a valid measure of walking performance.
Proceedings ArticleDOI

Evolving virtual creatures

Karl Sims
TL;DR: A genetic language is presented that uses nodes and connections as its primitive elements to represent directed graphs, which are used to describe both the morphology and the neural circuitry of creatures that move and behave in simulated three-dimensional physical worlds.
Journal ArticleDOI

From swimming to walking with a salamander robot driven by a spinal cord model.

TL;DR: A spinal cord model and its implementation in an amphibious salamander robot is presented that demonstrates how a primitive neural circuit for swimming can be extended by phylogenetically more recent limb oscillatory centers to explain the ability of salamanders to switch between swimming and walking.