Daniel Renjewski

Don't break a leg: running birds from quail to ostrich prioritise leg safety and economy on uneven terrain

Cursorial ground birds are paragons of bipedal running that span a 500-fold mass range from quail to ostrich. Here we investigate the task-level control priorities of cursorial birds by analysing how they negotiate single-step obstacles that create a conflict between body stability (attenuating deviations in body motion) and consistent leg force–length dynamics (for economy and leg safety). We also test the hypothesis that control priorities shift between body stability and leg safety with increasing body size, reflecting use of active control to overcome size-related challenges. Weight-support demands lead to a shift towards straighter legs and stiffer steady gait with increasing body size, but it remains unknown whether non-steady locomotor priorities diverge with size. We found that all measured species used a consistent obstacle negotiation strategy, involving unsteady body dynamics to minimise fluctuations in leg posture and loading across multiple steps, not directly prioritising body stability. Peak leg forces remained remarkably consistent across obstacle terrain, within 0.35 body weights of level running for obstacle heights from 0.1 to 0.5 times leg length. All species used similar stance leg actuation patterns, involving asymmetric force–length trajectories and posture-dependent actuation to add or remove energy depending on landing conditions. We present a simple stance leg model that explains key features of avian bipedal locomotion, and suggests economy as a key priority on both level and uneven terrain. We suggest that running ground birds target the closely coupled priorities of economy and leg safety as the direct imperatives of control, with adequate stability achieved through appropriately tuned intrinsic dynamics.

Impulsive ankle push-off powers leg swing in human walking.

Rapid unloading and a peak in power output of the ankle joint have been widely observed during push-off in human walking. Model-based studies hypothesize that this push-off causes redirection of the body center of mass just before touch-down of the leading leg. Other research suggests that work done by the ankle extensors provides kinetic energy for the initiation of swing. Also, muscle work is suggested to power a catapult-like action in late stance of human walking. However, there is a lack of knowledge about the biomechanical process leading to this widely observed high power output of the ankle extensors. In our study, we use kinematic and dynamic data of human walking collected at speeds between 0.5 and 2.5 m s−1 for a comprehensive analysis of push-off mechanics. We identify two distinct phases, which divide the push-off: first, starting with positive ankle power output, an alleviation phase, where the trailing leg is alleviated from supporting the body mass, and second, a launching phase, where stored energy in the ankle joint is released. Our results show a release of just a small part of the energy stored in the ankle joint during the alleviation phase. A larger impulse for the trailing leg than for the remaining body is observed during the launching phase. Here, the buckling knee joint inhibits transfer of power from the ankle to the remaining body. It appears that swing initiation profits from an impulsive ankle push-off resulting from a catapult without escapement.

ATRIAS: Design and validation of a tether-free 3D-capable spring-mass bipedal robot

ATRIAS is a human-scale 3D-capable bipedal robot designed to mechanically embody the spring-mass model for dynamic walking and running. To help bring the extensive work on this theoretical model further into practice, we present the design and validation of a spring-mass robot that can operate in real-world settings (i.e. off-tether and without planarizing restraints). We outline the mechanisms and design choices necessary to meet these specifications, particularly ATRIAS’ four-bar series-elastic leg design. We experimentally demonstrate the following robot capabilities, which are characteristics of the target model. 1) We present the robot’s physical capability for both grounded and aerial gaits, including planar walking and sustained hopping, while being more efficient than similarly gait-versatile bipeds. 2) The robot can be controlled by enforcing quantities derived from the simpler spring-mass model, such as leg angles and leg forces. 3) ATRIAS replicates the center-of-mass dynamics of human hopping and (novelly) walking, a key spring-mass model feature. Lastly, we present dynamically stable stepping in 3D without external support, demonstrating that this theoretical model has practical potential for real-world locomotion.

Exciting Engineered Passive Dynamics in a Bipedal Robot

A common approach in designing legged robots is to build fully actuated machines and control the machine dynamics entirely in software, carefully avoiding impacts and expending a lot of energy. However, these machines are outperformed by their human and animal counterparts. Animals achieve their impressive agility, efficiency, and robustness through a close integration of passive dynamics, implemented through mechanical components, and neural control. Robots can benefit from this same integrated approach, but a strong theoretical framework is required to design the passive dynamics of a machine and exploit them for control. For this framework, we use a bipedal spring-mass model, which has been shown to approximate the dynamics of human locomotion. This paper reports the first implementation of spring-mass walking on a bipedal robot. We present the use of template dynamics as a control objective exploiting the engineered passive spring-mass dynamics of the ATRIAS robot. The results highlight the benefits of combining passive dynamics with dynamics-based control and open up a library of spring-mass model-based control strategies for dynamic gait control of robots.

Robots in human biomechanics - a study on ankle push-off in walking

In biomechanics, explanatory template models are used to identify the basic mechanisms of human locomotion. However, model predictions often lack verification in a realistic environment. We present a method that uses template model mechanics as a blueprint for a bipedal robot and a corresponding computer simulation. The hypotheses derived from template model studies concerning the function of heel-off in walking are analysed and discrepancies between the template model and its real-world anchor are pointed out. Neither extending the ground clearance of the swinging leg nor an impact reduction at touch-down as an effect of heel lifting was supported by the experiments. To confirm the relevance of the experimental findings, a comparison of robot data to human walking data is discussed and we speculate on an alternative explanation of heel-off in human walking, i.e. that the push-off powers the following leg swing.

From Biomechanical Concepts Towards Fast And Robust Robots

Robots of any kind, highly integrated mechatronic systems, are smart combinations of mechanics, electronics and information technology. The development of bipedal robots in particular, which perform human-like locomotion, challenges scientists on even higher levels. Facing this challenge, this article presents a biomimetic bottom-up approach to use knowledge of biomechanical experiments on human walking and running, computer simulation and neuronal control concepts to sequentially design highly adaptable and compliant walking machines.

Open-Source Real-Time Robot Operation and Control System for Highly Dynamic, Modular Machines

The control system of a highly dynamic robot requires the ability to respond quickly to changes in the robot’s state. This type of system is needed in varying fields such as dynamic locomotion, multicopter control, and human-robot interaction. Robots in these fields require software and hardware capable of hard real-time, high frequency control. In addition, the application outlined in this paper requires modular components, remote guidance, and mobile control. The described system integrates a computer on the robot for running a control algorithm, a bus for communicating with microcontrollers connected to sensors and actuators, and a remote user interface for interacting with the robot. Current commercial solutions can be expensive, and open source solutions are often time consuming. The key innovation described in this paper is the building of a control system from existing - mostly open source - components that can provide realtime, high frequency control of the robot. This paper covers the development of such a control system based on ROS, OROCOS, and EtherCAT, its implementation on a dynamic bipedal robot, and system performance test results.

Compliant ankles and flat feet for improved self-stabilization and passive dynamics of the biped robot “RunBot”

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.

Effects of a neuromuscular controller on a powered ankle exoskeleton during human walking

Wearable devices to assist abnormal gaits require controllers that interact with the user in an intuitive and unobtrusive manner. To design such a controller, we investigated a bio-inspired walking controller for orthoses and prostheses. We present (i) a Simulink neuromuscular control library derived from a computational model of reflexive neuromuscular control of human gait with a central pattern generator (CPG) extension, (ii) an ankle reflex controller for the Achilles exoskeleton derived from the library, and (iii) the mechanics and energetics of healthy subjects walking with an actuated ankle orthosis using the proposed controller. As this controller was designed to mimic human reflex patterns during locomotion, we hypothesize that walking with this controller would lead to lower energetic costs, compared to walking with the added mass of the device only, and allow for walking at different speeds without explicit control. Preliminary results suggest that the neuromuscular controller does not disturb walking dynamics in both slow and normal walking cases and can also reduce the net metabolic cost compared to transparent mode of the device. Reductions in tibialis anterior and soleus activity were observed, suggesting the controller could be suitable, in future work, for augmenting or replacing normal walking functions. We also investigated the impedance patterns generated by the neuromuscular controller. The validity of the equivalent variable impedance controller, particularly in stance phase, can facilitate serving subject-specific features by linking impedance measurement and neuromuscular controller.

The development of a biomechanical leg system and its neural control

The function of the locomotor system in human gait is still an open question. Today robot bipeds are not able to reproduce the versatility of human locomotion. In this article a robotic knee joint and an experimental setup are proposed. The leg function is tested and the acquired data is compared to human leg behaviour in running observed in experiments.