Day by day, biped robots’ usage is increasing enormously in all industrial and non-industrial applications due to their ability to move in any unstructured environment compared to wheeled robots. Keeping this in mind, worldwide, many researchers are working on various aspects of biped robots, such as gait generation, dynamic balance margin, and the design of controllers. The main aim of this review article is to discuss the main challenges encountered in the biped gait generation and design of various controllers while moving on different terrain conditions such as flat, ascending and descending slopes or stairs, avoiding obstacles/ditches, uneven terrain, and an unknown environment. As per the authors’ knowledge, no single study has been carried out in one place related to the gait generation and design of controllers for each joint of the biped robot on various terrains. This review will help researchers working in this field better understand the concepts of gait generation, dynamic balance margin, and the design of controllers while moving on various terrains. Moreover, the current article will also cover the different soft computing techniques used to tune the gains of the controllers. In this article, the authors have reviewed a vast compilation of research work on the gait generation of the biped robot on various terrains. Further, the authors have proposed taxonomies on various design issues identified while generating the gait in different aspects. The authors reviewed approximately 296 articles and discovered that all researchers attempted to generate the dynamically balanced biped gait on various terrains.

Biped robots with dynamic motion control have shown strong robustness in complex environments. However, many motion planning methods rely on models, which have difficulty dynamically modifying the walking cycle, height, and other gait parameters to cope with environmental changes. In this study, a heuristic model-free gait template planning method with dynamic motion control is proposed. The gait trajectory can be generated by inputting the desired speed, walking cycle, and support height without a model. Then, the stable walking of the biped robot can be realized by foothold adjustment and whole-body dynamics model control. The gait template can be changed in real time to achieve gait flexibility of the biped robot. Finally, the effectiveness of the method is verified by simulations and experiments of the biped robot BHR-B2. The research presented here helps improve the gait transition ability of biped robots in dynamic locomotion.

In this paper, a new type of biped mobile robot is designed. Each leg of the robot is a 6 degree-of-freedom (DOF) parallel mechanism, and each leg has three relatively fixed landing points. The leg’s structure gives the robot better performance on large carrying capacity, strong environmental adaptability and fast moving speed simultaneously. At the same time, it helps the robot move more steadily and change direction more simply. Based on the structural features of the leg, the inverse kinematics model of the biped robot is established and a unified formula is obtained. According to an analysis of robot’s workspace, gait planning is completed and simulated. Finally, the special case that the robot can keep the upper body horizontal while walking on a slopy surface is validated.

This paper proposes a new design of robust control combining feedback linearization, backstepping, and sliding mode control called FLBS applied to the locomotion of five-link biped robot. Due to the underactuated robot’s model, the system has a hybrid nature, while the FLBS control can provide a stabilized walking movement even with the existence of large disturbances and uncertainties by implementing smooth chatter-free signals. Stability of the method is proven using the Lyapunov theorem based on the hybrid zero dynamics and Poincaré map. The simulations show the controller performance such as robustness and chatter-free response in the presence of uncertainty and disturbance.

This paper focuses on robust control of a simplest passive model, which is established on a DCLF (discrete control Lyapunov function) -based control system, and presents gait transition method based on the study of purely passive walker. Firstly, the DCLF is introduced to stabilize walking process between steps exponentially by modulating the length of next step. Next, the swing leg trajectory from mid-stance position to foot-strike can be planned. Then the control law is calculated to resist external disturbance. Besides, an impulse is added just before foot-strike to realize a periodic walking pattern on flat or uphill ground. With walking terrain varying, the robot can transit to an adaptive walking gait in a few steps. With different push or pull disturbances acting on hip joint and the robot gait transiting on a continuously slope-changing downhill, the effectiveness of the presented DCLF-based method is verified using simulation experiments. The ability to walk on a changing environment is also presented by simulation results. The insights of this paper can help to develop a robust control method and adaptive walking of dynamic passive locomotion robots.

Ditch crossing is one of the essential capabilities required for a biped robot in disaster management and search and rescue operations. Present work focuses on crossing a wide ditch with landing uncertainties by an under-actuated planar biped robot with five degrees of freedom. We consider a ditch as wide for a robot when the ankle to ankle stretch required to cross it is at least equal to the leg length of the robot. Since locomotion in uncertain environments requires real-time planning, in this paper, we present a new approach for generating real-time joint trajectories using control constraints not explicitly dependent on time, considering impact, dynamic balance, and friction. As part of the approach, we introduce a novel concept called the point of feasibility for bringing the biped robot to complete rest at the end of ditch crossing. We present a study on the influence of initial posture on landing impact and net energy consumption. Through simulations, we found the best initial postures to efficiently cross a wide ditch of width 1.05 m, with less impact and without singularities. Finally, we demonstrate the advantage of the proposed approach to cross a wide ditch when the surface friction is not same on both sides of the ditch.

One of the primary goals of biped locomotion is to generate and execute joint trajectories on a corresponding step plan that takes the robot from a start point to a goal while avoiding obstacles and consuming as little energy as possible. Past researchers have studied trajectory generation and step planning independently, mainly because optimal generation of robot gait using dynamic formulation cannot be done in real time. Also, most step-planning studies are for flat terrain guided by search heuristics. In the proposed method, a framework for generating trajectories as well as an overall step plan for navigation of a 12 degrees of freedom biped on an uneven terrain with obstacles is presented. In order to accomplish this, a dynamic model of the robot is developed and a trajectory generation program is integrated with it using gait variables. The variables are determined using a genetic algorithm based optimization program with the objective of minimizing energy consumption subject to balance and kinematic constraints of the biped. A database of these variables for various terrain angles and walking motions is used to train two neural networks, one for real-time trajectory generation and another for energy estimation. To develop a global navigation strategy, a weighted A* search is used to generate the footstep plan with energy considerations in sight. The efficacy of the approach is exhibited through simulation-based results on a variety of terrains.

This paper investigates the active vertical motion of biped systems and its significance to the balance of biped robots, which have been commonly neglected by the use of a well-known model called the Linear Inverted Pendulum Model. The feasible step location is theoretically estimated by considering the active vertical movement on a simple point mass model. Based on the estimation, we present two new strategies, namely the flexion strategy and the extension strategy, to enable biped robots to restore balance through active upward and downward motions. The analytical results demonstrate that the robot is able to recover from much larger disturbances using our proposed methods. Simulations of the simple point mass model validate our analysis. Besides, prototype controllers that incorporate our proposed strategies have also been implemented on a simulated humanoid robot. Numerical simulations on both the simple point mass model and the realistic humanoid model prove the effectiveness of proposed strategies.

In this article, a two-dimensional analysis of biped robot sliding dynamics is performed. First, the dynamics of a biped robot based on feet-slip are derived using the coulomb friction model. The state transition can be formulated in the centroid acceleration space whose diagram is defined as a “triangle of sliding friction” (TSF). The TSF's characteristics are explained by focusing on comparison with the cone of friction which has a similar state decision diagram. Next, for the behavioral simulation of a concrete model, a 2-DOF biped robot is used to analyze the sliding features in terms of the asymmetry of the dynamics of each leg. Finally, the sliding characteristics are applied to the two tasks of running and somersaulting. The results show the robot takes short rapid repetitive steps for running based on frictional asymmetry and theoretically based on torque asymmetry can make one revolution using the large angular momentum acquired during sliding motion.

Researchers dream of developing autonomous humanoid robots which behave/walk like a human being. Biped robots, although complex, have the greatest potential for use in human-centred environments such as the home or office. Studying biped robots is also important for understanding human locomotion and improving control strategies for prosthetic and orthotic limbs. Control systems of humans walking in cluttered environments are complex, however, and may involve multiple local controllers and commands from the cerebellum. Although biped robots have been of interest over the last four decades, no unified stability/balance criterion adopted for stabilization of miscellaneous walking/running modes of biped robots has so far been available. The literature is scattered and it is difficult to construct a unified background for the balance strategies of biped motion. The zero-moment point (ZMP) criterion, however, is a conservative indicator of stabilized motion for a class of biped robots. Therefore, we offer a systematic presentation of multi-level balance controllers for stabilization and balance recovery of ZMP-based humanoid robots.

In this paper, we propose and examine a force-resisting balance control strategy for a walking biped robot under the application of a sudden unknown, continuous force. We assume that the external force is acting on the pelvis of a walking biped robot and that the external force in the z-direction is negligible compared to the external forces in the x- and y-directions. The main control strategy involves moving the zero moment point (ZMP) of the walking robot to the center of the robot's sole resisting the externally applied force. This strategy is divided into three steps. The first step is to detect an abnormal situation in which an unknown continuous force is applied by examining the position of the ZMP. The second step is to move the ZMP of the robot to the center of the sole resisting the external force. The third step is to have the biped robot convert from single support phase (SSP) to double support phase (DSP) for an increased force-resisting capability. Computer simulations and experiments of the proposed methods are performed to benchmark the suggested control strategy.

The balance control problem of planar bipedal robots during disturbed standing is investigated. Virtual holonomic constraints which specify the angles of actuated joints as a function of the rotation angle between the sole of the stance foot and the ground are recalled. These constraints enable the robot to avoid turnover during external disturbances similar to how a human being would react. Moreover, for a disturbance beyond the balance conditions for single-leg support, the robot changes to a double support posture to avoid turnover by the virtual holonomic constraints. Further, for a special kind of balance: standing on toe which leads to underactuation, we also give the design conditions of the virtual holonomic constraints.

Previous research has revealed that foot rotation of the supporting foot in a single support phase could increase walking speed. This paper presents a method for force-controlled bipeds to realize foot rotation by breaking the kinematic contact constraint between the supporting foot and the ground. An inverse dynamics controller is proposed to make the biped model controllable even when the constraint is broken. In addition, a linear inverted pendulum model is extended to make its ZMP adjustable so that the ZMP can be predefined as required. When the planned ZMP is in the toe, the kinematic contact constraint will be broken and foot rotation can be achieved. A walking simulation demonstrates the effectiveness of the proposed method.

This paper designs a biped robot to perform appropriate walking exercises according to the terrain, which then walks stably on a flat environment. The concept of fuzzy logic is combined with the Linear Quadratic Regulator (LQR) controller theory to design the best method to allow the biped robot system to have a balanced and stable gait. Traditional controllers are designed using mathematical models of physical systems, but a fuzzy controller is a physical system that uses an inexact mathematical model, which involves sets and membership functions. Fuzzy controllers use fuzzification, fuzzy control rules, and defuzzification. The method and theory of control: A stable gait for robots is achieved using inverse kinematics, fuzzy concepts, the LQR controller theory, path design, and the characteristics of a dynamic equation. It is then simulated using mathematical tools to prove that the system eliminates swinging by biped robots without fuzzy control knowing beforehand the dynamic model the system is using. Proportional-Integral-Differential control achieves a stable gait design in a flat environment.

Passive walking robots can walk on a slight downward slope powered only by gravity. We propose a novel control strategy based on forced entrainment to stabilize a three-dimensional quasi-passive walking robot in uphill and level walking by using torso control in the frontal plane and synchronization of lateral motion with swing leg motion. We investigated the robot's walking energy efficiency, energy transformation, and transfer in simulation. The results showed that the proposed method is effective and energy-efficient for uphill and level walking. The relationship between energy utilization rate of actuation and energy efficiency of the robot was revealed, and mechanical energy transformation and transfer were characterized.

In this study, we attempt to develop a biped dinosaur-like walking robot by focusing on its nervous system as well as its mechanism. We developed a robot ‘Dinobot’ on the basis of palaeontological knowledge on dinosaurs and extant animals. In addition, we employed typical biologically inspired walking gait generation and control methods derived from an extant vertebrate's nervous system. In particular, we utilized a central pattern generator (CPG), which is a locomotion rhythm generator in a vertebrate's spinal cord, to generate the robot's walking rhythm. Moreover, a reflex centre was placed below CPG and it produced joint torque of the legs in the swing and stance phases. Thus, we successfully achieved adaptive 3D dynamic walking generated by the interaction between the original mechanism of dinosaurs and the nervous system of extant animals. Our future goal is to find out a dinosaur's robust locomotive nervous system suitable for its mechanism.

Biped robots have gained much attention for decades. A variety of researches have been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. This paper discusses the main challenges encountered in the design of biped robots, such as modeling, stability and their walking patterns. The subject is difficult to deal with because the biped mechanism intervenes with mechanics, control, electronics and artificial intelligence. In this paper, we collect and introduce a systematic discussion of modeling, walking pattern generators and stability for a biped robot.

The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The control, the virtual stability of every subsystem and the stability of the entire robotic system are proved in this work. Then the computational complexity of the FAT is compared with the regressor-based approach. Despite the apparent advantage of the FAT in avoiding the regressor matrix, its computational complexity can result in difficulties in the implementation because of the representation of the dynamic matrices of the link subsystem by two large sparse matrices. In effect, the FAT-based adaptive VDC requires further work for improving the representation of the dynamic matrices of the target subsystem. Two case studies are simulated by Matlab/Simulink: a 2-R manipulator and a 6-DOF planar biped robot for verification purposes.

Zero moment point (ZMP) is the most popular concept that is applied to stabilize the gait motion of a biped robot. This paper utilizes ZMP with the augmented-reality (AR) method to improve the stability of gait motion of a biped robot. The 3ds Max computer software package is used to build a virtual robot. Under an achieved joint angle data of solid robot to produce an animation of the robot's trajectory, the joint angle data are transmitted to the virtual robot to analyze the offset of the trunk. Furthermore, this investigation adopts AR to allow the user to make direct comparisons between the solid and virtual robot before and after the gait motion is corrected. The animated trajectories of the virtual robot are compared and the relevant data provide feedback to the solid robot to adjust the joint angle and further correct its posture. The experimental results reveal that the proposed scheme can improve gait motion, even when the biped robot is affected by an unexpected loading disturbance. As well as improving the stability of gait motion of a biped robot, the results of this study can also be used to teach the application of the proposed method in a robotics class.