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Lower extremity exoskeletons have drawn much attention recently due to their potential ability to help the stroke and spinal cord injury patients to regain the ability of walking. However, the balance of the human-exoskeleton system (HES) remains a big challenge. Usually, patients use crutches to keep balance when they wear exoskeleton. However, the balance depends greatly on the patient's balance ability and will be inevitably poor occasionally, which often causes the landing in advance of HES. The purpose of this paper is to propose a real-time stepping gait trajectory planning method based on the hip height variation of the swing leg to solve the problem.

The hip height of the swing leg was analyzed and measured. The simulation with MATLAB and the experimental test with the prototype of the proposed gait were conducted to verify its feasibility.

With the proposed method, HES can achieve successful step even when the balance kept by crutches is poor.

Instead of actively avoiding the poor balance due to the instability caused by gravity, the method just modifies the stepping gait passively to avoid the landing in advance when the poor balance appears. In addition, it may not work well when the balance is too poor. Moreover, the proposed gait is just used in the initial stage of rehabilitation training. Besides, the step length of the gait must be limited for comfort.

A real-time stepping gait trajectory planning method based on the hip height variation of the swing leg is first proposed and its feasibility to avoid the landing in advance when the balance kept by the crutches is poor has been preliminary verified.

The purpose of this study is to present an optimization-based gait planning method for biped robots according to the conditions of terrain, which takes fully the relationship between walking stability margin and energy efficiency into account.

First, the authors newly designed a practical gait motion synthesis algorithm by using the optimal allowable zero moment point (ZMP) variation region (OAZR), which can generate different gait motions corresponding to different terrains based on the modifiability of ZMP in lateral (y-axis) direction. Second, an effective gait parameter optimization algorithm is performed to find the optimal set of key gait parameters (step length, duration time of gait cycle, average height of center of mass (CoM), amplitude of the vertical CoM motion and double support ratio), which maximizes either the walking stability margin or the energy efficiency with certain walking stability margin under practical constraints (mechanical constraints of all joint motors, geometric constraints, friction force limit and yawing moment limit) according to the conditions of terrain. Third, the necessary controllers for biped robots have been introduced briefly.

The experiment data and results are described and analyzed, showing that the proposed method was verified through simulations and implemented on a DRC-XT biped robot.

The main contribution is that the OAZR has been defined based on AZR, which could be used to plan and generate the various feasible gait motions to help a biped robot to adapt effectively to various terrains.

The purpose of this study is to test a chassis robot on rugged road cargo handling.

Attitude solution of D-H series robot gyroscope speed and acceleration sensor.

In identical experimental environments, hexapodal robots experience smaller deviations when using a four-footed propulsive gait from a typical three-footed gait for forward motion; for the same distance but at different speeds, the deviation basically keeps itself within the same range when the robot advances forward with four-foot propulsive gait; because the foot slide in the three-footed gait sometimes experiences frictions, the robot exhibits a large gap in directional deviations in different courses during motion; for motion using a four-footed propulsive gait, there are minor directional deviations of hexapodal robots resulting from experimental errors, which can be reduced through optimizing mechanical structures.

Planning different gaits can solve problems existing in some typical gaits. This article has put forward a gait planning method for hexapodal robots moving forward with diverse gaits as a redundant multifreedom structure. Subsequent research can combine a multiparallel-legged structure to analyze kinematics, optimize the robot’s mechanical structure and carry out in-depth research of hexapod robot gaits.

To achieve stable gait planning and enhance the motion performance of quadruped robot, this paper aims to propose a motion control strategy based on central pattern generator (CPG) and back-propagation neural network (BPNN).

First, the Kuramoto phase oscillator is used to construct the CPG network model, and a piecewise continuous phase difference matrix is designed to optimize the duty cycle of walk gait, so as to realize the gait planning and smooth switching. Second, the mapper between CPG output and joint drive is established based on BP neural network, so that the quadruped robot based on CPG control has better foot trajectory to enhance the motion performance. Finally, to obtain better mapping effect, an evaluation function is resigned to evaluate the proximity between the actual foot trajectory and the ideal foot trajectory. Genetic algorithm and particle swarm optimization are used to optimize the initial weights and thresholds of BPNN to obtain more accurate foot trajectory.

The method provides a solution for the smooth gait switching and foot trajectory of the robot. The quintic polynomial trajectory is selected to testify the validity and practicability of the method through simulation and prototype experiment.

The paper solved the incorrect duty cycle under the walk gait of CPG network constructed by Kuramoto phase oscillator, and made the robot have a better foot trajectory by mapper to enhance its motion performance.

The purpose of this paper is to present a coordinated control strategy for stable walking of biped robot with heterogeneous legs (BRHL), which consists of artificial leg (AL) and intelligent bionic leg (IBL).

The original concentrated control in common biped robot system is replaced by a master‐slave dual‐leg coordinated control. P‐type open/closed‐loop iterative learning control is used to realize the time‐varying gait tracking for IBL to AL.

The new control architecture can simplify gait planning scheme of BRHL system with complicated closed‐chain mechanism and mixed driving mode.

Designing and constructing a suitable magneto‐rheological damper can greatly improve the control performance of IBL.

Master‐slave coordination strategy is suitable for BRHL stable walking control.

The concepts and methods of dual‐leg coordination have not been explicitly proposed in single biped robot control research before. Master‐slave coordinated control strategy is suitable for complicated BRHL.

This paper aims to investigate an autonomous obstacle-surmounting method based on a hybrid gait for the problem of crossing low-height obstacles autonomously by a six wheel-legged robot. The autonomy of obstacle-surmounting is reflected in obstacle recognition based on multi-frame point cloud fusion.

In this paper, first, for the problem that the lidar on the robot cannot scan the point cloud of low-height obstacles, the lidar is driven to rotate by a 2D turntable to obtain the point cloud of low-height obstacles under the robot. Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping algorithm, fast ground segmentation algorithm and Euclidean clustering algorithm are used to recognize the point cloud of low-height obstacles and obtain low-height obstacle in-formation. Then, combined with the structural characteristics of the robot, the obstacle-surmounting action planning is carried out for two types of obstacle scenes. A segmented approach is used for action planning. Gait units are designed to describe each segment of the action. A gait matrix is used to describe the overall action. The paper also analyzes the stability and surmounting capability of the robot’s key pose and determines the robot’s surmounting capability and the value scheme of the surmounting control variables.

The experimental verification is carried out on the robot laboratory platform (BIT-6NAZA). The obstacle recognition method can accurately detect low-height obstacles. The robot can maintain a smooth posture to cross low-height obstacles, which verifies the feasibility of the adaptive obstacle-surmounting method.

The study can provide the theory and engineering foundation for the environmental perception of the unmanned platform. It provides environmental information to support follow-up work, for example, on the planning of obstacles and obstacles.

This study aims to present a type of metamorphic mechanism-based quadruped crawling robot. The trunk design of the robot has a metamorphic mechanism, which endows it with excellent crawling capability and adaptability in challenging environments.

The robot consists of a metamorphic trunk and four series-connected three-joint legs. First, the walking and steering strategy is planned through the stability and mechanics analysis. Then, the walking and steering performance is examined using virtual prototype technology, as well as the efficacy of the walking and turning strategy.

The metamorphic quadruped crawling robot has wider application due to its variable trunk configuration and excellent leg motion space. The robot can move in two modes (constant trunk and trunk configuration transformation, respectively, while walking and rotating), which exhibits outstanding stability and adaptability in the examination and verification of prototypes.

The design can enhance the capacity of the quadruped crawling robot to move across a complex environment. The virtual prototype technology verifies that the proposed walking and steering strategy has good maneuverability and stability, which considerably expands the application opportunity in the fields of complicated scene identification and investigation.

The purpose of this paper is specifically to provide a more intelligent locomotion planning method for a hexapod robot based on trajectory optimization, which could reduce the complexity of locomotion design, shorten time of design and generate efficient and accurate motion.

The authors generated locomotion for the hexapod robot based on trajectory optimization method and it just need to specify the high-level motion requirements. Here the authors first transcribed the trajectory optimization problem to a nonlinear programming problem, in which the specified motion requirements and the dynamics with complementarity constraints were defined as the constraints, then a nonlinear solver was used to solve. The leg compliance was taken into consideration and the generated motions were deployed on the hexapod robot prototype to prove the utility of the method and, meanwhile, the influence of different environments was considered.

The generated motions were deployed on the hexapod robot and the movements were demonstrated very much in line with the planning. The new planning method does not require lots of parameter-tuning work and therefore significantly reduces the cycle for designing a new locomotion.

A locomotion generation method based on trajectory optimization was constructed for a 12-degree of freedom hexapod robot. The variable stiffness compliance of legs was considered to improve the accuracy of locomotion generation. And also, different from some simulation work before, the authors have designed the locomotion in three cases and constructed field tests to demonstrate its utility.

At present, more than 100 million undetonated landmines left over from wars remain buried worldwide. These mines kill or injure approximately 3,000 individuals each year (80 persons per day), most of them civilians. They represent a particularly acute problem in developing countries and nations already economically hard hit by war. The problem of unexploded mines has become a serious international issue, with many people striving to find a solution. The purpose of this paper is to examine the requirements of the robotic systems for humanitarian demining purposes. It will discuss a hexapod walking robot developed at the Royal Military Academy of Brussels in collaboration with the Free University of Brussels, Belgium, in the framework of the Humanitarian Demining Project (HUDEM).

Considerations for the design of the walking robot according to the humanitarian demining requirements are discussed in detail.

A successful walking robot design for demining purposes must consider functional requirements relevant to this difficult application. The principal requirements are mentioned in this paper.

This paper is the result of the research of the HUDEM project team and it is of value to engineers and researchers developing robotic systems for humanitarian demining purposes.

The aim of this paper is to introduce a hexapod walking robot specifically designed for applications in humanitarian demining, intended to operate autonomously for several hours. To this end, the paper presents an experimental study for the evaluation of its energy efficiency.

First, the interest of using a walking robot for detection and localization of anti-personnel landmines is described, followed by the description of the mechanical system and the control architecture of the hexapod robot. Second, the energy efficiency of the hexapod robot is assessed to demonstrate its autonomy for performing humanitarian demining tasks. To achieve this, the power consumed by the robot is measured and logged, with a number of different payloads placed on-board (always including the scanning manipulator arm assembled on the robot front end), during the execution of a discontinuous gait on flat terrain.

The hexapod walking robot has demonstrated low energy consumption when it is carrying out several locomotion cycles with different loads on it, which is fundamental to have a desired autonomy. It should be considered that the robot has a mass of about 250 kg and that it has been loaded with additional masses of up to 170 kg during the experiments, with a consumption of mean power of 72 W, approximately.

This work provides insight on the use of a walking robot for humanitarian demining tasks, which has high stability and an autonomy of about 3 hours for a robot with high mass and high payload. In addition, the robot can be supervised and controlled remotely, which is an added value when it is working in the field.