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Gait adjusting is an effective way to solve leg failure problems and is also the foundation of intelligent self-adjustment. This paper takes a hexagonal type of robot as a prototype and proposes a ‘2-2-1’ gait grouping and gait sequence for the one leg failure case based on the ‘4 + 2’ gait. The longitudinal stability margin is used to evaluate the FLF-A and FLF-B gaits with left front leg failure and FLM-A and FLM-B gait with left middle leg failure. The foothold positions are adjusted by changing the median angle of the stance phase of the body-coxa joint in each leg in order to make sure the centre of gravity is in a stable support polygon. The experiments of the robot walking show that the FLF-A gait and the FLM-B gait are more stable than the FLF-B and FLM-A after adjustment. The pitch and roll angles are maintained within − 3° to 3°, which verify the effectiveness of the stance phase leg median position adjustment strategy. This study could be used to do forward pre-adjustment in the case of one leg failure. [ABSTRACT FROM AUTHOR]

This research focuses on designing a real-time, flexible gait planner for lower limb exoskeleton robots to assist patients with lower limb disabilities. Given the dynamic nature of gait parameters, which vary according to ground conditions and user intent, the challenge lies in developing a gait planner capable of adapting to these changes in real-time. To avoid planning complications in the cartesian space and to comply with the speed constraints of joint motors, this paper proposes planning in joint space. Furthermore, the approach also considers the maximum speed capabilities of the joint motors, aiming to generate an executable gait pattern and simultaneously enhance the robot’s walking speed by determining the minimum time required for implementation. The introduced gait planner optimizes joint trajectories for minimal angular acceleration. To provide flexibility, generalized boundary conditions suitable for different scenarios are defined. The effectiveness of the proposed planner is validated through comprehensive performance analysis, simulations, and successful implementation trials on the Exoped® robot in various scenarios. [ABSTRACT FROM AUTHOR]

Robots are becoming integral to society and industries due to their enormous advantages. Among the various categories of mobile robots, including wheeled robot, tracked robot, and legged robots, the latter stands out as a better choice for most field applications due to their adaptability across various terrains. The purpose of this review is to study the locomotion capabilities of quadruped robots and judge their suitability for climbing applications as most unexplored applications of automation and robotics are required to climb. This review explores the locomotion capabilities of quadruped robots. It covers different aspects of quadruped robots like types of legs, leg design, gait patterns, and their mathematical formulations, and types of motions like omnidirectional motion and body sway motion. It also emphasizes its fault-tolerant gait, adaptability, and reliability. The paper also focuses on slope and stair climbing, outlining design requirements and applications. The study includes an examination of the applicability of various gaits under different conditions and the methods for increasing stability without compromising speed. Overall, the review serves as a valuable resource for future research in this field. [ABSTRACT FROM AUTHOR]

This research aims to advance the current state-of-the-art of earthworm-like robots by extending the gait study from rectilinear and planar locomotion to spatial locomotion. In detail, the following five important but largely unaddressed issues are tackled in this paper, including the multibody kinematic modeling of the robot with spatial locomotion capability, 3D gait generation algorithm, spatial locomotion mode classification, spatial locomotion performance evaluation, and 3D gait planning. Based on the multibody model of the metameric earthworm-like robot and learning from the retrograde peristalsis wave, a gait-generation algorithm is proposed for generating all admissible 3D locomotion gaits. The 3D locomotion can be classified into four major types (rectilinear, sidewinding, circular, and cycloid), and further, ten modes with their defining conditions in terms of the gait parameters being derived. Among them, several spatial locomotion modes, such as the 3D cycloid locomotion, are uncovered for the first time. For each mode, different kinematic indexes, including the average (axial) velocity and the circumradius of the trajectory, are evaluated to comprehensively clarify the relationship between the locomotion performance and the gait parameters. Moreover, aiming at reaching the target both quickly and precisely, 3D gait planning is also studied. With contradictory objectives, the Pareto front is determined via the genetic algorithm so that a trade-off between the proximity and speed to the target can be achieved. [ABSTRACT FROM AUTHOR]

Gait planning is one of the main focuses in the research field of bipedal robotics. To enhance the stability and simplicity of gait planning for bipedal robots using central pattern generator (CPG) methods, this paper first refines the existing Kimura oscillator model. Subsequently, an improved oscillator model is employed to propose a novel configuration of CPG network for flat walking gait planning in bipedal robots. A particle swarm algorithm with variable structural parameters is utilized to optimize the parameters of the CPG network, with the optimization objective being the maximization of stability margin at zero moment points (ZMP) during the walking process of the bipedal robot. Finally, an ADAMS simulation experiment platform is established to validate the feasibility of this method through simulation experiments. The experimental results indicate that this approach enables bipedal robots to achieve stable walking motion on a flat surface. [ABSTRACT FROM AUTHOR]

The exoskeleton robot is a wearable electromechanical device inspired by animal exoskeletons. It combines technologies such as sensing, control, information, and mobile computing, enhancing human physical abilities and assisting in rehabilitation training. In recent years, with the development of visual sensors and deep learning, the environmental perception of exoskeletons has drawn widespread attention in the industry. Environmental perception can provide exoskeletons with a certain level of autonomous perception and decision-making ability, enhance their stability and safety in complex environments, and improve the human–machine–environment interaction loop. This paper provides a review of environmental perception and its related technologies of lower-limb exoskeleton robots. First, we briefly introduce the visual sensors and control system. Second, we analyze and summarize the key technologies of environmental perception, including related datasets, detection of critical terrains, and environment-oriented adaptive gait planning. Finally, we analyze the current factors limiting the development of exoskeleton environmental perception and propose future directions. [ABSTRACT FROM AUTHOR]

Robots are becoming integral to society and industries due to their enormous advantages. Among the various categories of mobile robots, including wheeled robot, tracked robot, and legged robots, the latter stands out as a better choice for most field applications due to their adaptability across various terrains. The purpose of this review is to study the locomotion capabilities of quadruped robots and judge their suitability for climbing applications as most unexplored applications of automation and robotics are required to climb. This review explores the locomotion capabilities of quadruped robots. It covers different aspects of quadruped robots like types of legs, leg design, gait patterns, and their mathematical formulations, and types of motions like omnidirectional motion and body sway motion. It also emphasizes its fault-tolerant gait, adaptability, and reliability. The paper also focuses on slope and stair climbing, outlining design requirements and applications. The study includes an examination of the applicability of various gaits under different conditions and the methods for increasing stability without compromising speed. Overall, the review serves as a valuable resource for future research in this field.

The commonly used finite-state-machine (FSM) impedance control for powered prostheses deploys diverse control parameters according to different gait phases, resulting in dozens of parameter adjustments and possible gait phase misrecognition. In contrast, this study presents a straightforward, continuous, and speed-adaptive control approach based on hip-knee motion-lagged coordination mapping (MLCM). The mapping, featured by the motion lag, can effectively generate the prosthetic knee’s goal gait within a second-order polynomial. It is also verified from extensive gait analysis that the motion lag and polynomial coefficients evolve linearly with respect to walking speed and gait period, promising a simple real-time deployment for prosthesis control. Experimental validation with two non-disabled subjects and two transfemoral amputees wearing a prosthesis demonstrates the MLCM controller’s ability to reduce the hip compensatory behavior, generate biomimetic knee kinematics, stance phase time, stride length, and hip-knee motion coordination across various speeds. Furthermore, compared to the benchmark FSM impedance controller, the MLCM controller reduces the number of control parameters from 17 to 7 and avoids misrecognition during gait phase transitions.

The hemiplegic patients can't walk on their own due to the movement obstacle of one side of the lower limb caused by brain injury. The lower limb wearable walker can help them get the ability to walk, but if they want to walk out the normal gait like ordinary people, the gait planning of the lower limb wearable walker is necessary. Gait planning is the basis and key for man-machine coupling walking and maintaining stability. Firstly, through the analysis of the movement of each joint of the lower limb, the overall mechanism of the lower limb wearable walker is designed. Secondly the gait planning is carried out. The part between the joints of the leg of the walker is regarded as a homogeneous rigid link, nine special time points of each joint in the complete walking cycle are extracted, and the coordinates and angles of the joints at each time point are analyzed. Combined with the cubic spline interpolation method in Matlab software, the motion track of the joints is simulated. Finally,the gait planning data is analyzed to obtain the coordinates of the barycenter projection point, fit the motion track of the barycenter projection point, and analyze whether the track always falls in the support area. The results prove that the barycenter projection point is always in the supporting area, which indicates that the gait planning meets the stability requirements.

We present WCQR-III, an untethered bioinspired climbing robot capable of versatile locomotion, including ground walking, wall climbing and ground-to-wall transition. Inspired by gecko lizards, WCQR-III features a structure comprising four feet and one tail. The foot design incorporates a switching mechanism to seamlessly transition between walking and climbing modes. A spiny claw provides wall adhesion, while a rubber pad offers friction and cushioning for ground walking. Leveraging the screw theory, we establish a kinematic model to analyze the robot's mobility and transition ability. In the walking mode, a trotting gait is adopted, while the climbing mode introduces a detaching angle, pause, and backswing movement of spiny toes, facilitating easy detachment from surfaces. An offline search algorithm optimizes the motion trajectory. Mobility analysis of different configurations confirms that a crouched posture is necessary for successful ground-to-wall transition. Experimental verification on WCQR-III demonstrates a maximum speed of 0.46 m/s on horizontal ground, 0.23 m/s on vertical walls, and successful achievement of ground-to-wall transition. [ABSTRACT FROM AUTHOR]

The exoskeleton robot is a wearable electromechanical device inspired by animal exoskeletons. It combines technologies such as sensing, control, information, and mobile computing, enhancing human physical abilities and assisting in rehabilitation training. In recent years, with the development of visual sensors and deep learning, the environmental perception of exoskeletons has drawn widespread attention in the industry. Environmental perception can provide exoskeletons with a certain level of autonomous perception and decision-making ability, enhance their stability and safety in complex environments, and improve the human–machine–environment interaction loop. This paper provides a review of environmental perception and its related technologies of lower-limb exoskeleton robots. First, we briefly introduce the visual sensors and control system. Second, we analyze and summarize the key technologies of environmental perception, including related datasets, detection of critical terrains, and environment-oriented adaptive gait planning. Finally, we analyze the current factors limiting the development of exoskeleton environmental perception and propose future directions.

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soft robots demonstrate an impressive ability to adapt to objects and environments. However, current soft mobile robots often use a single mode of movement. This gives soft robots good locomotion performance in specific environments but poor performance in others. In this paper, we propose a leg–wheel mechanism inspired by bacterial flagella and use it to design a leg–wheel robot. This mechanism employs a tendon-driven continuum structure to replicate the bacterial flagellar filaments, while servo and gear components mimic the action of bacterial flagellar motors. By utilizing twisting and swinging motions of the continuum structure, the robot achieves both wheeled and legged locomotion. The paper provides comprehensive descriptions and detailed kinematic analysis of the mechanism and the robot. To verify the feasibility of the robot, a prototype was implemented, and experiments were performed on legged mode, wheeled mode, and post-overturning motion. The experimental results demonstrate that the robot can achieve legged and wheeled motions. Moreover, it is also demonstrated that the robot still has mobility after overturning. This expands the applicability scenarios of the current soft mobile robot. [ABSTRACT FROM AUTHOR]

A kinematics analysis of a new hybrid mechanical leg suitable for bipedal robots was carried out and the gait of the robot walking on flat ground was planned. Firstly, the kinematics of the hybrid mechanical leg were analyzed and the applicable relevant models were established. Secondly, based on the preliminary motion requirements, the inverted pendulum model was used to divide the robot walking into three stages for gait planning: mid-step, start and stop. In the three stages of robot walking, the forward and lateral robot centroid motion trajectories and the swinging leg joint trajectories were calculated. Finally, dynamic simulation software was used to simulate the virtual prototype of the robot, achieving its stable walking on flat ground in the virtual environment, and verifying the feasibility of the mechanism design and gait planning. This study provides a reference for the gait planning of hybrid mechanical legged bipedal robots and lays the foundation for further research on the robots involved in this thesis. [ABSTRACT FROM AUTHOR]

Abstract This paper presents an effective way to support motion planning of legged mobile robots—Inverted Modelling, based on the equivalent metamorphic mechanism concept. The difference from the previous research is that we herein invert the equivalent parallel mechanism. Assuming the leg mechanisms are hybrid links, the body of robot being considered as fixed platform, and ground as moving platform. The motion performance is transformed and measured in the body frame. Terrain and joint limits are used as input parameters to the model, resulting in the representation which is independent of terrains and particular poses in Inverted Modelling. Hence, it can universally be applied to any kind of legged robots as global motion performance framework. Several performance measurements using Inverted Modelling are presented and used in motion performance evaluation. According to the requirements of actual work like motion continuity and stability, motion planning of legged robot can be achieved using different measurements on different terrains. Two cases studies present the simulations of quadruped and hexapod robots walking on rugged roads. The results verify the correctness and effectiveness of the proposed method.

The rapid development of science and technology promotes the intensive development of robotics and the application of ADAMS in the field of robotics is constantly expanding. Research on robot kinematics and dynamics is the core issue of biped robot animation simulation. It is of great significance to propose an efficient and improved inverse kinematics algorithm for the development of robotic bionics in China. In this paper, the BIOLOID robot assembly kit is used as the research platform. Based on this, the biped robot kinematics equations and dynamic equations are deduced, and a three-step programming method is used to carry out reasonable gait planning for the biped robot. A simplified virtual prototype model of the lower limb of a biped robot, and the motion trajectories of the joints are input to perform motion simulation of the robot's static walking. The feasibility of gait planning is verified by analyzing the dynamic images obtained from the simulation experiments and the experimental data of each joint vector. This paper uses the Denavit-Hartenberg rule to construct a biped robot animation simulation kinematics model, deduces a matrix expression describing joint vectors between adjacent links, and solves the biped robot's positive kinematics equation by chain multiplication rule; An efficient and improved inverse kinematics algorithm is proposed. This solution has the characteristics of high accuracy, high efficiency and few redundant solutions. The experimental study found that the three-step planning method for biped robotic static walking planning is feasible and can reach 98%, and can meet the pre-planning requirements. [ABSTRACT FROM AUTHOR]

The humanoid robots have similar human feet, but due to the limitations of joint freedom, they are difficult to walk on the special ground like humans, so planning an effective walking method applies on these special grounds becomes of critical importance. As a typical example of a special ground, this paper proposes a dynamic planning method for the gait planning problem of the humanoid robot NAO climbing and down stairs. Firstly, the NAO robot is modeled by the kinematics; then it can be understood the humanoid robot itself after the gait characteristics and human walking patterns according to the characteristics of the stairs, and the geometric constraints of the robot's walking gaits on the stairs are analyzed; further then the robot's lateral gait is planned through a first-order linear inverted pendulum model, and the variable length model is used. The inverted pendulum model is used to plan the forward gait of the robot, and then the start and stop gaits of the robot are planned respectively and meanwhile we proposed the zero-moment point stability judgment and the supporting polygons control to determine whether the robot is in a stable state. In the three-dimensional stairs, the visual system of the NAO robot was used to perceive its surrounding environment, and then the image processing technology was used to identify the position of the stairs. Finally, the correctness of the gait planning is verified by the Webots Platform for NAO simulation and its real operation. The experimental results show that the gait planning method used in this paper is highly feasible. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents an effective way to support motion planning of legged mobile robots—Inverted Modelling, based on the equivalent metamorphic mechanism concept. The difference from the previous research is that we herein invert the equivalent parallel mechanism. Assuming the leg mechanisms are hybrid links, the body of robot being considered as fixed platform, and ground as moving platform. The motion performance is transformed and measured in the body frame. Terrain and joint limits are used as input parameters to the model, resulting in the representation which is independent of terrains and particular poses in Inverted Modelling. Hence, it can universally be applied to any kind of legged robots as global motion performance framework. Several performance measurements using Inverted Modelling are presented and used in motion performance evaluation. According to the requirements of actual work like motion continuity and stability, motion planning of legged robot can be achieved using different measurements on different terrains. Two cases studies present the simulations of quadruped and hexapod robots walking on rugged roads. The results verify the correctness and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

To implement the various movement control of the hexapod robot, a motion controller based on the double-layered central pattern generator (CPG) is proposed in this paper. The novel CPG network is composed of a rhythm layer and a pattern layer. The CPG neurons are constructed based on Kuramoto nonlinear oscillator. The parameters including the frequency, coupling strength, and phase difference matrix of the CPG network for four typical gaits are planned. The mapping relationship between the signals of the CPG network and the joint trajectories of the hexapod robot is designed. The co-simulations and experiments have been conducted to verify the feasibility of the proposed CPG-based controller. The actual average velocities of the wave gait, the tetrapod gait, the tripod gait, and the self-turning gait are 10.8 mm/s, 25.5 mm/s, 37.8 mm/s and 26°/s, respectively. The results verify that the hexapod robot with the proposed double-layered CPG-based controller can perform stable and various movements. [ABSTRACT FROM AUTHOR]

The hexapod wall climbing robots have the advantages of traversing complex wall surfaces. To traverse complex environments autonomously, it must possess the capability to select gait parameters and paths appropriate for the wall surface. Path planning and gait optimization is a fundamental issue in the aspect of stable, energy efficient robot navigation in complex environments with static and dynamic obstacles. Traditional statistical models have been developed to get the optimal path and gait parameters but the result obtained was very poor. Metaheuristic algorithms are gaining importance in robotic gait planning. In this paper, we proposed robust two stage gait planning approach for predicting collision-free, distance-minimal, smooth navigation path and ensuring stable, energy efficient gait patterns for robots using hybrid metaheuristic algorithms. In the first stage, optimal climbing path for robot is predicted using Tri-objective Grey Wolf Path Optimization (TGWPO) based on obstacle and target detection. In the second stage, the gait parameters adaptive to the constructed climbing path are optimized using Adaptive multi-objective Particle swarm optimization (AMPSO). The hexapod wall climbing robot is designed with STM32F103 as core controller modeled with optimal path planner (using TDWPO) and gait optimizer module (using AMPSO). STM32F103 controller commands and controls the robot to climb on wall with optimized gait parameters according to the optimal path. We analyzed the efficacy of the proposed two stage gait planning approach using TDWPO-AMPSO for hexapod wall climbing robots with existing gait planning approaches in terms of path length, climbing time, gait stability, obstacle avoidance, and energy efficiency. The result analysis showed that the suggested gait planning approach is efficient over conventional strategies for climbing robots. [ABSTRACT FROM AUTHOR]

Due to their high kinematic characteristics, six-bar tensegrities have great potential application value in the field of robotics, especially in the field of deep space exploration robots. In this paper, an ultralight six-bar tensegrity robot is designed, and a gait planning method for continuous motion is proposed. First, the equilibrium matrix of the tensegrity structure is constructed, and singular value decomposition (SVD) is performed to find the node coordinates and internal forces of the tensegrity structure. Two representative examples regarding tensegrity structures are presented to demonstrate the capability of the proposed method in the initial selfstress design that satisfies the stability of tensegrities. Furthermore, both the principal rolling analysis and gait planning are also addressed based on the offset of the center of gravity. A six-bar tensegrity robot prototype is developed, and the obstacle avoidance experiment is completed. Finally, the results show that the six-bar tensegrity robot has good kinematic performance. Moreover, this robot is expected to play a key role in future planetary exploration. [ABSTRACT FROM AUTHOR]

This article develops a gait planning method for underactuated bipedal robot on uneven and compliant terrain. First, we employ a linear spring-damper model to describe foot-ground compliant contact, and establish a decoupled robot–ground three-dimensional dynamic mode. Second, based on a velocity-based bipedal stability definition and human walking characteristics, we propose a gait planning method to realize underactuated bipedal walking on uneven and compliant terrain. We decouple bipedal gait planning into sagittal and lateral master-slave ones. By planning the motion state of Center-of-Mass (CoM) of a robot, we make the movement of lateral and sagittal coincident such that bipedal walking is realized. Finally, underactuated bipedal walking with an average walking speed of 0.216 m/s and a step length of 183.9 mm is realized on uneven terrain where the maximum height of unevenness is 32 mm. The experimental results show that underactuated bipedal walking can be realized on uneven and compliant terrain by using the proposed method to control robot CoM and track its desired velocity. [ABSTRACT FROM AUTHOR]

In this paper, a compliant control scheme based on the optimization of the contact force of the robot leg is proposed to improve the stability of the whole moving process of the robot. Firstly, according to the motion state of the robot, the change of its center of gravity is analyzed, then the stable gait of the robot is determined by the stability margin, and the smooth control of the robot's foot trajectory is realized. Finally, the compliant control model of the robot leg is established. In the process of moving, the contact force between the legs and the ground is optimized in real-time, so that the composite robot can walk steadily on uneven terrain. The 3-D model of the scorpion composite robot was built with ADAMS software, and dynamics simulation was carried out according to the compliant control scheme. This paper takes the robot's walking speed and torso angle as performance evaluation indexes and verifies the effectiveness of the compliant control scheme. The cooperative motion stability test is carried out on the actual uneven terrain. The test results show that the robot's pitch angle and roll angle are between ±0.5°, which meets the motion stability requirements of the robot and verifies the correctness of the compliant control scheme and control model proposed in this paper. [ABSTRACT FROM AUTHOR]

Aiming at the straight and turning movements of quadruped robots， the gait based on the crawling gait is separately planned. The concept of coordinated rotating gait is proposed and used it in in-situ turning. The common point of the foot trajectory of the straight gait and the turning gait on the spot is found， and then this point is used to realize the rapid migration of the gait and use it in the turning motion of the quadruped robot. According to the structure design of the quadruped robot in the early stage， a virtual prototype of a quadruped robot is established. A new evaluation criterion—angle margin criterion （SA criterion） is proposed to evaluate the stability of its planned gait， so as to find the optimal gait. A test platform is set up for testing， and the results showed that the gait planning for straight and turning is reasonable and feasible.

Soft robots demonstrate an impressive ability to adapt to objects and environments. However, current soft mobile robots often use a single mode of movement. This gives soft robots good locomotion performance in specific environments but poor performance in others. In this paper, we propose a leg–wheel mechanism inspired by bacterial flagella and use it to design a leg–wheel robot. This mechanism employs a tendon-driven continuum structure to replicate the bacterial flagellar filaments, while servo and gear components mimic the action of bacterial flagellar motors. By utilizing twisting and swinging motions of the continuum structure, the robot achieves both wheeled and legged locomotion. The paper provides comprehensive descriptions and detailed kinematic analysis of the mechanism and the robot. To verify the feasibility of the robot, a prototype was implemented, and experiments were performed on legged mode, wheeled mode, and post-overturning motion. The experimental results demonstrate that the robot can achieve legged and wheeled motions. Moreover, it is also demonstrated that the robot still has mobility after overturning. This expands the applicability scenarios of the current soft mobile robot.

A kinematics analysis of a new hybrid mechanical leg suitable for bipedal robots was carried out and the gait of the robot walking on flat ground was planned. Firstly, the kinematics of the hybrid mechanical leg were analyzed and the applicable relevant models were established. Secondly, based on the preliminary motion requirements, the inverted pendulum model was used to divide the robot walking into three stages for gait planning: mid-step, start and stop. In the three stages of robot walking, the forward and lateral robot centroid motion trajectories and the swinging leg joint trajectories were calculated. Finally, dynamic simulation software was used to simulate the virtual prototype of the robot, achieving its stable walking on flat ground in the virtual environment, and verifying the feasibility of the mechanism design and gait planning. This study provides a reference for the gait planning of hybrid mechanical legged bipedal robots and lays the foundation for further research on the robots involved in this thesis.

In order to perform various complex tasks in place of humans, humanoid robots should walk robustly in the presence of interference. In the paper, an improved model predictive control (MPC) method based on the divergent components of motion (DCM) is proposed. Firstly, the humanoid robot model is simplified to a finite-sized foot-pendulum model. Then, the gait of the humanoid robot in the single-support phase (SSP) and double-support phase (DSP) is planned based on DCM. The center of mass (CoM) of the robot will converge to the DCM, which simplifies the feedback control process. Finally, an MPC controller incorporating an extended Kalman filter (EKF) is proposed to realize the tracking of the desired DCM trajectory. By adjusting the step duration, the controller can compensate for CoM trajectory errors caused by disturbances. Simulation results show that—compared with the traditional method—the method we propose achieves improvements in both disturbed walking and uneven-terrain walking. [ABSTRACT FROM AUTHOR]

Based on the human structure as the prototype， a humanoid robot with a lower limb and 7 degrees of freedom is designed based on bionics. The motion coordinates of human body during normal walking are collected through the three-dimensional optical motion capture system， and the joint angle and the variation rule of the moment of each lower extremity joint during walking are obtained by analyzing the data. A 7-degree-of-freedom kinematics model of the lower extremity is established and inverse kinematics analysis is carried out to solve the variation of the lower extremity joint angles. According to the gait programming， the rotation angles of the lower extremity joints during the humanoid robot walking are solved. In the lower extremity in UG environment， the 3D model of 7 DOF humanoid robot is established， and the dynamics simulation is carried out by using multi-body dynamics software Adams， combining with the gait motion planning from the angle of the changing situation to set the simulation parameters， through virtual prototype humanoid robot gait， and the simulation data and the data results from the motion capture experimental are compared. Research results show， the humanoid robot can achieve stable walking gait， the overall accuracy of the modeling ideas， analysis of kinematics and dynamics simulation is confirmed. Based on the results of the experiment simulation for hip and knee torque value compared with the experimental value of relative error of 6.7% and 9.6% respectively in a reasonable scope， the basis for the humanoid robot structure design and motor selection is provided.

To deal with the problem of stable walking of quadruped robots on slopes, a gait planning algorithm framework for quadruped robots facing unknown slopes is proposed. We estimated the terrain slope by the attitude information measured by the inertial measurement unit (IMU) without relying on the robot vision. The crawl gait was adopted, and the center of gravity trajectory planning was carried out based on the stability criterion zero-moment point (ZMP). Then, the augmented random search (ARS) algorithm was used to modulate the parameters of the Bezier curve to realize the planning of the robot foot trajectory. Additionally, the robot can adjust the posture in real time to follow the desired joint angle, which realizes the adaptive adjustment of the robot's posture during the slope movement. Simulation experiment results show that the proposed algorithm for slope gait planning can adaptively adjust the robot's attitude and stably pass through the slope environment when the slope is unknown. [ABSTRACT FROM AUTHOR]