Narrow Results

Planar information is crucial for determining the support plane of a candidate footstep, enabling reliable traversability checks during footstep planning. Due to the imprudent determination of the support plane caused by insufficient planar information, current heightmap-based algorithms struggle to plan footsteps in discontinuous coplanar terrain. In this paper, we propose a plane-aware heightmap that integrates the results of planar region detection, allowing each cell to direct retrieval of its corresponding plane parameters. Building on this, the support plane of a candidate footstep is determined by evaluating the consistency between the support planes of the four corner subregions of the foot. Specifically, the support plane considered for each corner subregion is the one with the highest elevation within that region, provided it is sufficiently large to support the corresponding area. We evaluate the enhancement of footstep planning achieved by the proposed heightmap and support-plane determination methods, which enable planning across diverse discontinuous coplanar terrain in both simulated and real-world settings.

Many studies have been done on different aspects of biped robots such as motion, path planning, control and stability. Dynamical properties of biped robot on a sloping surface such as equilibria and their stabilities, bifurcations and basin of attraction are investigated in this paper. Basin of attraction is an important property since it can determine the unseen conditions which affect the attractor of the system with multistabilities. By the help of basin of attractions, the paper claims that the strange attractors of compass-gait robot are hidden.

Human lower limbs have particular flexibility. Both the efficiency of bipedal walking and the ability to protect actuators with low energy loss are worthy references for the design of bipedal robots. This paper proposes a design for a biped robot with joints of variable stiffness. The robot has three degrees of freedom in the sagittal plane in each leg. The hips and knees are driven directly by the motor, while the ankles are passive joints with adjustable stiffness. After a comprehensive investigation, a variable stiffness mechanism was introduced based on lever principles, and driven by a motor that can realize real-time adjustment. Simulations verified the necessity of variable stiffness joints in the robot. The variable stiffness joint can absorb the ground impact on each joint, reduce the energy loss of the motor, and improve the efficiency of movement.

This paper presents a new reference trajectory and a fuzzy wavelet neural network controller to synthesize the gait of a five-link biped robot when walking on the level ground. Both the single support phase (SSP) and the double support phase (DSP) are considered. The gait of the biped can be determined when the trajectories of the hip and the swing limb are designed. The trajectories of the hip and the swing limb are approximated with the time polynomial functions. The coefficients of the functions are determined by the constraint equations cast in terms of coherent physical characteristics, such as repeatability, continuity, stability, and minimization of the effect of impact. The fuzzy wavelet neural network controller is trained by error back-propagation algorithm. Given the certain gait parameters such as the step length, maximum step height, walking speed, and so on, the control scheme can generate the smooth gait profiles. The simulation results show that the designed controller can follow the reference trajectories well.

The biped robot "Johnnie" is designed to achieve a dynamically stable gait pattern, allowing for high walking velocities. Very accurate and fast sensors were developed for the machine. In particular the design of the 3D-orientation sensor and the 6-axes force-torque sensor are presented. The control scheme is based on the information from these sensors to deal with unstructured terrain and disturbances. Two different implementations are investigated: a computed torque approach and a trajectory control with adaptive trajectories. Walking speeds of 2.2 km/h have been achieved in experiments.

In the present paper, two algorithms based on soft computing have been developed for dynamically balanced gait generations of a biped robot ascending and descending a staircase. The utility of the soft computing tools is best justified, when the data available for the problem to be solved are imprecise in nature, difficult to model and exhibit large-scale solution spaces. The problem of online gait generation of a biped robot exhibits such a complex phenomenon, and ultimately soft computing has become a natural choice for solving it. The gait generation problems of a biped robot have been solved using two different approaches, namely genetic-neural (GA-NN) and genetic-fuzzy (GA-FLC) systems. In GA-NN, the gait generation problem of a two-legged robot has been modeled using two modules of Neural Network (NN), whose weights are optimized offline using a Genetic Algorithm (GA), whereas in GA-FLC, the above problem is modeled utilizing two modules of Fuzzy Logic Controller (FLC) and their rule bases are optimized offline using a GA. Once optimized, the GA-NN and GA-FLC systems will be able to generate dynamically balanced gaits of the biped robot online. The performances of the two approaches are compared with respect to the Dynamic Balance Margin (DBM).

The present paper deals with dynamically balanced ascending and descending gait generations of a 7 DOF biped robot negotiating a staircase. During navigation, the foot of the swing leg is assumed to follow a trajectory, after ensuring its kinematic constraints. Dynamic balance margin of the gaits are calculated by using the concept of zero-moment point (ZMP). In the present work, an approach different from the well-known semi-inverse method has been developed for trunk motion generation, in which it is initially generated based on static balance and then checked for its dynamic balance. The joint torques are determined utilizing the Lagrange–Euler formulation, and the average power consumption at each joint is calculated. Moreover, variations of the dynamic balance margin are studied for both the ascending as well as descending gaits of the biped robot. Average dynamic balance margin and average power consumption in the ascending gait are found to be more than that of the descending gait. The effect of trunk mass on the dynamic balance margin and average power consumption for both the ascending and descending gaits are studied. The dynamic balance margin and average power consumption are found to decrease and increase, respectively with the increase in the trunk mass.

This paper presents a simple computational technique to generate ZMP compliant gait trajectories for seven-mass biped robots with no torso. The generation of such ZMP compliant trajectories for one- and three-mass approximations of biped robots have been developed earlier and presented elsewhere. In a one-mass case, the hip is assumed to move according to a self-compensating pattern. In a three-mass case, the swinging foot has been made to perform the prescribed motion and rest of the body is used as the compensating motion. In this work, it is reasoned that such simple techniques are not applicable for seven-mass representation, due to the complexity of the structure. One needs to make realistic approximations without losing model relevance. It is suggested that by sensibly ganging the motion of primitive limb elements, an effective solution can be facilitated. With simple iterative computations, ZMP compliant body trajectories are obtained. Patterns generated by this method agree with earlier solutions obtained by others.

The moving torso plays an important role in the dynamics of bipeds like human beings, the exploitation of which is the essential focus of this paper. A design is presented where the torso is actuated to make the biped walk with the required step-length while allowing the legs to move passively. A periodic response excitation is achieved and the motion of the torso is optimized with respect to the external energy input. A working model of the biped is designed and built in which only the torso is actuated and the legs are passive. This laboratory model is used to test and validate the analytical solutions.

Stability analysis is one of the main issues in the research area of biped robots with point feet. This article develops stability analysis and robust control of a planar biped robot with point feet with one degree of underactuation. A stability analysis is presented for the bipedal motion comprising single support and impact phases by using Poincaré map for nonlinear systems. Then, the stability conditions of periodic orbits are derived and stable gait pattern is determined using an optimization process. Thereafter, a robust sliding mode control with a time-invariant feedback is proposed to track stable gait in the presence of parameter uncertainties of the biped. Proposed approach is carried out for two types of bipeds, namely, a normal model and a balanced model in which the biped center of mass located at the hip using a novel model. Energy efficiency of biped is investigated for both models. Moreover, the stability of biped motion is studied in the presence of an unexpected stair. Simulation results show the biped motion quickly converges to cyclic motion during the first gait in both models.

This paper, describes the development of a motion capture system with novel features for biped robots. In general, motion capture is effectively utilized in the field of computer animation. In the field of humanoid robotics, the number of studies attempting to design human-like gaits by using expensive optical motion capture systems is increasing. The optical motion capture systems used in these studies have involved a large number of cameras because such systems use small-sized ball markers; hence the position accuracy of the markers and the system calibration are very significant. However, since the human walking gait is a simple periodic motion rather than a complex motion, we have developed a specialized motion capture system for this study using dual video cameras and large band-type markers without high-level system calibration in order to capture the human walking gait. In addition to its lower complexity, the proposed capture method requires only a low-cost system and has high space efficiency. An image processing algorithm is also proposed for deriving the human gait data. Finally, we verify the reliability and accuracy of our system by comparing a zero moment point (ZMP) trajectory calculated by the motion captured data with a ZMP trajectory measured by foot force sensors.

This paper proposes an energy control method for dynamic obstacle crossing by a planar biped. This approach was tested in a simulation where it was found to enable the biped robot to cross obstacles of different heights, due to inertial forces, by leaning with the front foot on the obstacles. The propulsion energy of the system is produced by the rear leg, which is endowed with four actuated degrees-of-freedom (hip, knee, ankle, toes), and is controlled by force control with four degrees-of-freedom in the non-singular case, and three degrees-of-freedom in the singular case. This paper identifies ten geometric, energetic and servo-control parameters necessary for dynamic obstacle crossing. The methodology presented allowed the dynamic crossing of an obstacle up to 20 cm high, at which point the joint torque limit for the propelling ankle was reached.

This paper introduces two new important issues to be considered in the design of the zero moment point (ZMP) trajectory of a biped robot. It was verified experimentally that in the human gait the ZMP trajectory moves along the foot in a way that it is shifted forward relative to its center. To take this into account a shift parameter is then proposed. It was also verified experimentally that in the human gait the ZMP trajectory amplitude depends on the swing time, reducing to zero for a static gait. It is then proposed a parameter to take into account this variation with the swing time of the gait. Six experiments were carried out for three different X_ZMP trajectory references. In order to evaluate and compare the performance of the biped robot using the three X_ZMP trajectory references two performance indexes are proposed. For the real-time balance control of this 8 link biped robot it was used an intelligent computing control technique, the Support Vector Regression (SVR). The control method uses the ZMP error and its variation as inputs and the output is the correction of the robot's ankle and torso angles, necessary for the sagittal balance of the biped robot.

Most of current biped robots are active walking platforms. Though they have strong locomotion ability and good adaptability to environments, they have a lot of degrees of freedom (DoFs) and hence result in complex control and high energy consumption. On the other hand, passive or semi-passive walking robots require less DoFs and energy, but their walking capability and robustness are poor. To overcome these shortcomings, we have developed a novel active biped walking robot with only six DoFs. The robot is built with six 1-DoF joint modules and two wheels as the feet. It achieves locomotion in special gaits different from those of traditional biped robots. In this paper, this novel biped robot is introduced, four walking gaits are proposed, the criterion of stable walking is addressed and analyzed, and walking patterns and motion planning are presented. Experiments are carried out to verify the locomotion function, the effectiveness of the presented gaits and to illustrate the features of this novel biped robot. It has been shown that biped active walking may be achieved with only a few DoFs and simple kinematic configuration.

Moving the torso laterally in a walking biped robot can be mechanically more torque-efficient than not moving the torso according to recent research. Motivated by this observation, a torque-efficient torso-moving balance control strategy of a walking biped robot subject to a persistent continuous external force is suggested and verified in this paper. The torso-moving balance control strategy consists of a preliminary step and two additional steps. The preliminary step (disturbance detection) is to perceive the application of an external force by a safety boundary of zero moment point, detected approximately from cheap pressure sensors. Step 1 utilizes center of gravity (COG) Jacobian, centroidal momentum matrix and linear quadratic problem calculation to shift the zero moment point to the center of the support polygon. Step 2 makes use of H_∞ controllers for a more stable state shift from single support phase to double support phase. By comparing the suggested torso moving control strategy to the original control strategy that we suggested previously, a mixed balance control strategy is suggested. The strategy is verified through numerical simulation results.

In this paper, we propose a force-resisting balance control strategy for a walking biped robot subject to an unknown continuous external force. We assume that the biped robot has 12 degrees of freedom (DOFs) with position-controlled joint motors, and that the unknown continuous external force is applied to the pelvis of the biped robot in the single support phase (SSP) walking gait. The suggested balance control strategy has three phases. Phase 1 is to recognize the application of an unknown external force using only zero moment point (ZMP) sensors. Phase 2 is to control the joint motors according to a method that uses a genetic algorithm and the linear interpolation technique. Against an external continuous force, the robot retrieves the pre-calculated solutions and executes the desired torques with interpolation performed in real time. Phase 3 is to make the biped robot move from the SSP to the double support phase (DSP), rejecting external disturbances using the sliding mode controller. The strategy is verified by numerical simulations and experiments.

This paper presents a control method of the torso for dynamic walking of biped robots. Specifically, we want to save the energy and improve the walking stability by the planning and control of torso orientation at landing. First, the impact process of leg exchange is formulated using a simplified model. Based on this, the influence of the torso orientation at landing on walking performance is investigated. Second, a control method of torso orientation, which is an under actuated control, is proposed to regulate the torso orientation in the single support phase (SSP). Third, the control module of the torso is integrated into the previously established control frame of 3D biped walking to implement the control objective of a 3D humanoid robot. The results of a number of simulations show the feasibility of the proposed method, and also explore the relations between the speed, stability and energy consumption with the landing orientation of the torso.

This paper introduces the design methodology, the modeling and the power consumption tests for a newly developed biped robot equipped with 12 DOFs. The robot is 1.1 meters tall (lower limbs) which makes it comparable in dimension with other state-of-the-art full-scale humanoids. By using a combination of 3D printing techniques and lightweight materials, the system weighs only 10.8kg (without batteries) while retaining high links strength and rigidity. Without compromising the workspace dimension, the robot presents a very low weight-to-height ratio (9.8kg/m) that translates into a safer operation and reduced energy consumption. To perform elementary locomotion primitives, e.g., changing the support from one foot to the other or lifting its body, the robot prototype consumes only 65 watts. Simulation results demonstrate the suitability of the robot’s kinematics to perform walking motion and predict an average power consumption of 200 watts. The direct kinematics of the robot is presented together with its inverse dynamics based on a Chaotic Recurrent Neural Network (CRNN). The adaptive model is identified using a recursive least squares algorithm that allows the CRNN to predict the torques at different step lengths with a MSE of 0.0057 on normalized data.

The adaptation of a biped’s foot motion to the ground conditions and maintaining stability of the robot is an undeniable necessity that is the focus of this research. In this research, dynamics equations will be obtained for single support phase (SSP), double support phase (DSP), and impact. The results of impact dynamics have been used to correlate the gait parameters with the contact event following impact. In this study, in addition to explaining impact equations for a nine-link biped robot with toe and heel in first and second impact phases, a clear response for the external impulses is obtained in a compact form for the first time. In this paper, the trajectory of the foot and toe is done by determining the constraints of motion parameters with and without impact effect. Then, a method based on smooth hip motion with the largest stability margin using only two parameters, is implemented through iterative calculations, to ensure stability of the robot in accordance with the criterion of zero-moment point (ZMP). Finally, the response of a model-based controller, called feed-forward algorithm (FA), and a non-model-based controller, called the transposes Jacobian algorithm (TJ), will be used to control the robot.

This paper presents a hierarchical controller and extracts the singular configurations based on underactuated system and optimal distribution of forces. Unlike multi-legged and large-sole robots, biped robot with point contact cannot maintain a stable standing state, much less to adjust attitude and resist external impact. The support domain of point-foot bipedal robot degenerates into a line segment consisting of two footholds, introducing the underdactuated characteristic that challenges traditional algorithms based on polygonal domains and full variable optimization. To fully exploit the dynamic connection between support line and balance control, the accurate model is established as feedforward terms using virtual leg and floating reference system. The dynamics model is decomposed into an underactuated module and a force distribution module for hierarchical control, in which the former determines the control forces of base and the singularity corresponding to robot configuration, and the latter distributes forces on each leg according to its capability by solving a quadratic programming with constraints. The results verify the advanced stability of attitude adjustment and impact from external force of biped robot with point contact comparing to model predictive control, which is improved based on robot’s singular configuration.