Review of Quadruped Robots for Dynamic Locomotion

This review introduces quadruped robots: MITCheetah, HyQ, ANYmal, BigDog, and their mechanical structure, actuation, and control

Quasi Optimal Gait of a Biped Robot with a Rolling Knee Kinematic

In this paper, we address the problem of optimization of trajectories for a new class of biped robot. The knees of this biped are similar as the anthropomorphic one and have a rolling contact between the femur and the tibia. The robot has seven mechanical links and six actuators. The walking gait considered is a succession of single support phase (SSP) and impact of the mobile foot with the ground. Cubic uniform spline functions defined on a time interval express the gait for one step. An energy consumption function and a torques quadratic function are used to compare the new robot with anthropomorphic knees to a conventional robot with revolute joint knees. The minimization of the criteria is made with simplex algorithm. The physical constraints concerning the ZMP and the mobile foot behavior are respectively checked to make a step. Simulation results show that the energy consumption of the new biped with rolling knee contact is less than that of the robot with revolute joint knees.ANR R2A

On the Role of Sensory Feedbacks in Rowat–Selverston CPG to Improve Robot Legged Locomotion

This paper presents the use of Rowat and Selverston-type of central pattern generator (CPG) to control locomotion. It focuses on the role of afferent exteroceptive and proprioceptive signals in the dynamic phase synchronization in CPG legged robots. The sensori-motor neural network architecture is evaluated to control a two-joint planar robot leg that slips on a rail. Then, the closed loop between the CPG and the mechanical system allows to study the modulation of rhythmic patterns and the effect of the sensing loop via sensory neurons during the locomotion task. Firstly simulations show that the proposed architecture easily allows to modulate rhythmic patterns of the leg, and therefore the velocity of the robot. Secondly, simulations show that sensori-feedbacks from foot/ground contact of the leg make the hip velocity smoother and larger. The results show that the Rowat–Selverston-type CPG with sensory feedbacks is an effective choice for building adaptive neural CPGs for legged robots

3LP: a linear 3D-walking model including torso and swing dynamics

In this paper, we present a new model of biped locomotion which is composed of three linear pendulums (one per leg and one for the whole upper body) to describe stance, swing and torso dynamics. In addition to double support, this model has different actuation possibilities in the swing hip and stance ankle which could be widely used to produce different walking gaits. Without the need for numerical time-integration, closed-form solutions help finding periodic gaits which could be simply scaled in certain dimensions to modulate the motion online. Thanks to linearity properties, the proposed model can provide a computationally fast platform for model predictive controllers to predict the future and consider meaningful inequality constraints to ensure feasibility of the motion. Such property is coming from describing dynamics with joint torques directly and therefore, reflecting hardware limitations more precisely, even in the very abstract high level template space. The proposed model produces human-like torque and ground reaction force profiles and thus, compared to point-mass models, it is more promising for precise control of humanoid robots. Despite being linear and lacking many other features of human walking like CoM excursion, knee flexion and ground clearance, we show that the proposed model can predict one of the main optimality trends in human walking, i.e. nonlinear speed-frequency relationship. In this paper, we mainly focus on describing the model and its capabilities, comparing it with human data and calculating optimal human gait variables. Setting up control problems and advanced biomechanical analysis still remain for future works.Comment: Journal paper under revie

Robust Tracking of Bio-Inspired References for a Biped Robot Using Geometric Algebra and Sliding Mode Control

Controlling walking biped robots is a challenging problem due to its complex and uncertain dynamics. In order to tackle this, we propose a sliding mode controller based on a dynamic model which was obtained using the conformal geometric algebra approach (CGA). The CGA framework permits us to use lines, points, and other geometric entities, to obtain the Lagrange equations of the system. The references for the joints of the robot were bio-inspired in the kinematics of a walking human body. The first and second derivatives of the reference signal were obtained through an exact robust differentiator based on high order sliding mode. The performance of the proposed control schemes are illustrated through simulation.ITESO, A.C