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The purpose of this systematic review is to report the characteristics and methods utilized in human lower limb or knee joint only biomechanical models to provide state-of-the-art knowledge on the topic. This review was conducted according to the preferred reporting items for systematic reviews and meta-analyses guidelines. PubMed, Scopus and Web of Science were searched up to 24th April 2018 to look for musculoskeletal models of the human lower limb or knee joint only without any associated pathology. A 15-item checklist was used to assess the methodological quality of the included studies. Twenty-one studies were included, with seventeen of them modelling the lower limb and four only the knee joint. The methodological quality of the studies varied considerably, with the reporting of model characteristics showing very low quality. Among studies including experimental setup, subjects were instructed to perform vertical jumping, running at different speeds, drop landing and isokinetic knee extension (5%), static conditions (9%), knee’s flexion/extension (14%) and walking at constant (29%) and different (33%) speeds. A great variety of modelling strategies was found for the reproduction of the human musculoskeletal system in terms of number of segments, muscles and muscle models. The reviewed musculoskeletal models were able to reproduce human movement dynamics similar to results present in literature and to experimentally measured records. However, standardized methods for reporting the characteristics and methods of these models are missing and should be addressed in future studies.

This work comprises the use of a biomechanical model of the human lower limb proposed by Geyer and Herr in 2010, possessing the reproduction of the human skeletal, muscular and neural systems to simulate human gait. This approach was used to study characteristic parameters at joint level, such as range of motion and torques, during physiological and anterior cruciate ligament (ACL) pathological gait. The model kinematics when simulating healthy gait were in very good agreement with kinematics reported in literature. Regarding to the kinetics, the ankle joint torque plot was corroborated with literature, whilst the hip and knee torques presented differences both in magnitude and in shape. The implementation of pathology consisted of penalizing the torque produced by the muscles, namely the quadriceps and hamstrings, affected by an ACL injury after surgical reconstruction and rehabilitation. Healthy and pathological cases were compared. The variable closer to literature was the knee angle, whilst the other kinetic and kinematic data differed. This strategy aims at aiding the development of more efficient rehabilitation strategies to be prescribed after an ACL injury. These and other issues will be object of study in the context of this investigation.

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.

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.

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.

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.

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.