Generation of a continuous free gait for quadruped robot over rough terrains

Generating a robust gait is one of the most important factors to improve the adaptability of quadruped robots on rough terrains. This paper presents a new continuous free gait generation method for quadruped robots capable of walking on the rough terrain characterized by the uneven ground and forbidden areas. When walking with the proposed gait, the robot can effectively maintain its stability by using the Center of Gravity (COG) trajectory planning method. After analyzing the point cloud of rough terrain, the forbidden areas of the terrain can be obtained. Based on this analysis, an optimal foothold search strategy is presented to help quadruped robot to determine the optimum foothold for the swing foot automatically. In addition, the foot sequence determining method is proposed to improve the performance of robot. With the free gait proposed in this paper, quadruped robot can walk through the rough terrains automatically and successfully. The correctness and effectiveness of the proposed method is verified via simulations.     

Improving traversability of quadruped walking robots using body movement in 3D rough terrains

This paper presents a study on improving the traversability of a quadruped walking robot in 3D rough terrains. The key idea is to exploit body movement of the robot. The position and orientation of the robot are systematically adjusted and the possibility of finding a valid foothold for the next swing is maximized, which makes the robot have more chances to overcome the rough terrains. In addition, a foothold search algorithm that provides the valid foothold while maintaining a high traversability of the robot, is investigated and a gait selection algorithm is developed to help the robot avoid deadlock situations. To explain the algorithms, new concepts such as reachable area, stable area, potential search direction, and complementary kinematic margin are introduced, and the effectiveness of the algorithms is validated via simulations and experiments.     

Gait planning and intelligent control for a quadruped robot

We present a method for designing free gaits for a structurally symmetrical quadruped robot capable of performing statically stable, omnidirectional walking on irregular terrain. The robot＇s virtual model is constructed and a control algorithm is proposed by applying virtual components at some strategic locations. The deliberative-based controller can generate flexible sequences of leg transferences while maintaining walking speed, and choose optimum foothold for moving leg based on integration data of exteroceptive terrain profile. Simulation results are presented to show the gait＇s efficiency and system＇s stability in adapting to an uncertain terrain.     

A fault tolerant gait for a hexapod robot over uneven terrain

The fault tolerant gait of legged robots in static walking is a gait which maintains its stability against a fault event preventing a leg from having the support state. In this paper, a fault tolerant quadruped gait is proposed for a hexapod traversing uneven terrain with forbidden regions, which do not offer viable footholds but can be stepped over. By comparing performance of straight-line motion and crab walking over even terrain, it is shown that the proposed gait has better mobility and terrain adaptability than previously developed gaits. Based on the proposed gait, we present a method for the generation of the fault tolerant locomotion of a hexapod over uneven terrain with forbidden regions. The proposed method minimizes the number of legs on the ground during walking, and foot adjustment algorithm is used for avoiding steps on forbidden regions. The effectiveness of the proposed strategy over uneven terrain is demonstrated with a computer simulation.     

Quadruped robot trotting over irregular terrain assisted by stereo-vision

Legged robots have the potential to navigate in challenging terrain, and thus to exceed the mobility of wheeled vehicles. However, their control is more difficult as legged robots need to deal with foothold computation, leg trajectories and posture control in order to achieve successful navigation. In this paper, we present a new framework for the hydraulic quadruped robot HyQ, which performs goal-oriented navigation on unknown rough terrain using inertial measurement data and stereo-vision. This work uses our previously presented reactive controller framework with balancing control and extends it with visual feedback to enable closed-loop gait adjustment. On one hand, the camera images are used to keep the robot walking towards a visual target by correcting its heading angle if the robot deviates from it. On the other hand, the stereo camera is used to estimate the size of the obstacles on the ground plane and thus the terrain roughness. The locomotion controller then adjusts the step height and the velocity according to the size of the obstacles. This results in a robust and autonomous goal-oriented navigation over difficult terrain while subject to disturbances from the ground irregularities or external forces. Indoor and outdoor experiments with our quadruped robot show the effectiveness of this framework.     

Weaver: Hexapod robot for autonomous navigation on unstructured terrain

Legged robots are an efficient alternative for navigation in challenging terrain. In this paper we describe Weaver, a six‐legged robot that is designed to perform autonomous navigation in unstructured terrain. It uses stereo vision and proprioceptive sensing based terrain perception for adaptive control while using visual‐inertial odometry for autonomous waypoint‐based navigation. Terrain perception generates a minimal representation of the traversed environment in terms of roughness and step height. This reduces the complexity of the terrain model significantly, enabling the robot to feed back information about the environment into its controller. Furthermore, we combine exteroceptive and proprioceptive sensing to enhance the terrain perception capabilities, especially in situations in which the stereo camera is not able to generate an accurate representation of the environment. The adaptation approach described also exploits the unique properties of legged robots by adapting the virtual stiffness, stride frequency, and stride height. Weaver's unique leg design with five joints per leg improves locomotion on high gradient slopes, and this novel configuration is further analyzed. Using these approaches, we present an experimental evaluation of this fully self‐contained hexapod performing autonomous navigation on a multiterrain testbed and in outdoor terrain.     

Whole-body motion planning and control of a quadruped robot for challenging terrain

Quadruped robots working in jungles, mountains or factories should be able to move through challenging scenarios. In this paper, we present a control framework for quadruped robots walking over rough terrain. The planner plans the trajectory of the robot's center of gravity by using the normalized energy stability criterion, which ensures that the robot is in the most stable state. A contact detection algorithm based on the probabilistic contact model is presented, which implements event-based state switching of the quadruped robot legs. And an on-line detection of contact force based on generalized momentum is also showed, which improves the accuracy of proprioceptive force estimation. A controller combining whole body control and virtual model control is proposed to achieve precise trajectory tracking and active compliance with environment interaction. Without any knowledge of the environment, the experiments of the quadruped robot SDUQuad-144 climbs over significant obstacles such as 38 cm high steps and 22.5 cm high stairs are designed to verify the feasibility of the proposed method.     

Application of Localization Based on the DC Magnetic Field that Occurs in the Environment on Wheel-Type Mobile Agricultural Robots

A wheel-type mobile robot is simply able to localize with odometry. However, for mobile agricultural robots, it is necessary to consider that the environment is uneven terrain. Therefore, odometry is unreliable and it is necessary to augment the odometry by measuring the position of the robot relative to known objects in the environments. This paper describes the application of localization based on the DC magnetic field that occurs in the environment on mobile agricultural robots. In this research, a magnetic sensor is applied to scan the DC magnetic field to build a magnetic database. The robot localizes by matching magnetic sensor readings against the magnetic database. The experimental results indicate that the robot is able to localize accurately with the proposed method and the cumulative error can be eliminated by applying the localization results to compensate for the odometry.     

Steady Crawl Gait Generation Algorithm for Quadruped Robots

The capability of stable walking on irregular terrain is the primary advantage of legged robots over wheeled mobile robots. However, the traditional foothold selection-based gait generation algorithms are not suitable at some points for blind robots which cannot obtain the exact terrain information. A velocity-based gait generation algorithm with real-time adaptation rules which are necessary for steady walking is suggested. Particularly, we have developed a steady crawl gait with duty factor β = 0.75. The main feature of the suggested algorithm is that it is not based on foothold selection and it can be used for the walking of blind robots on more realistic irregular terrain. The adaptation rules are the translational velocity modification to satisfy the steady gait requirement and the swing period modification to avoid the kinematic limitation. The suggested gait generation algorithm has been implemented in a simple quadruped robot that has a total of eight actuated joints on the legs. Using PD controllers for each actuated joint for the trajectory following and the adaptation algorithm of gait parameters, the steady periodic crawl gait on irregular terrain has been demonstrated.     

The Design and Control of a Prototype Quadruped Microrover

We describe the design, construction and control of a quadruped robot which walks on uneven terrain. A control system which produces a statically stable gait has been implemented; results showing a straight and turning gait are presented. The control of quadruped robots poses interesting challenges due to a small stability margin (when compared to hexapods for example). For this reason most implemented systems for outdoor walking on uneven terrain have been hexapods. The system described here has the added virtue of using very few inexpensive sensors and actuators. One of the aims of this work is to build a reduced complexity (low power, low mass and direct drive) walking robot for statically stable walking. The other aim is to compare the performance of this robot with a wheeled robot roughly the same size and weight. In this paper we report on progress towards the first of these two goals using a traverse across an obstacle field as an example.     

Crab walking of quadruped robots with a locked joint failure

Fault tolerance is an important aspect in the development of control systems for multi-legged robots since a failure in a leg may lead to a severe loss of static stability of a gait. In this paper, an algorithm for tolerating a locked joint failure is described in gait planning for a quadruped robot with crab walking. A locked joint failure is one for which a joint cannot move and is locked in place. If a failed joint is locked, the workspace of the resulting leg is constrained, but legged robots have fault tolerance capability to continue walking maintaining static stability. A strategy for fault-tolerant gaits is described and, especially, a periodic gait is presented for crab walking of a quadruped. The leg sequence and the formula of the stride length are analytically driven based on gait study and robot kinematics. The adjustment procedure from a normal gait to the proposed fault-tolerant crab gait is shown to demonstrate the applicability of the proposed scheme.     

Neural networks IC controlled multi-legged walking MEMS robot with independent leg mechanism

In this paper, we will compare the walking behavior of quadruped and hexapod walking MEMS robots. These robots are fabricated by connecting same modules, which are composed of a couple of independent leg mechanisms. Independent leg mechanisms can actuate the single leg by a single artificial muscle wire. The neural networks IC that mimics real living organisms controls the mechanical systems. The length and weight of the quadruped MEMS robot were 7.2 mm and 95.8 mg, respectively. The quadruped robot showed the walking speed of 24.6 mm/min. The robot tended to lose its balance and the weight balance is quite important for the moving quadruped. On the other hand, the length and weight of the hexapod MEMS robot were 9.0 mm and 162 mg, respectively. The hexapod robot showed stable walking. The speed was 27.0 mm/min.     

Application of parallel mechanism in varistructured quadruped/biped human-carrying walking chair robot

For the existing problems of walking chair robot such as simple function,lower bearing capacity and not walking in complex environment,a novel varistructured quadruped / biped human-carrying walking chair robot is proposed.The proposed robot could be used as biped and quadruped walking chair robots.Considering the conversion of the walking chair robot from the quadruped to the biped or vice versa,6-UPS and 2-UPS+UP(U,P and S are universal joint,the prismatic pair,and sphere joint,respectively) parallel mechanisms are selected as the leg mechanism of the biped walking robot and quadruped walking robot,respectively.Combining the screw theory and theory of mechanism,the degrees of freedom of the leg mechanism and the body mechanism in diferent motion states are computed so as to meet the requirements of mechanism design.The motion characteristics of the 2-UPS+UP parallel mechanism which is the key part of the walking chair robot are analyzed.Then,the workspace of the moving platform is drawn and the efect of the structural parameters on the workspace volume is studied.Finally,it is found that the volume of the workspace of the moving platform is bigger when the side length ratio and the vertex angle ratio of the fxed platform and the moving platform which are isosceles triangles are close to 1.This study provides a theoretical foundation for the prototype development.     

Rough terrain mapping and classification for foothold selection in a walking robot

Although legged locomotion over a moderately rugged terrain can be accomplished by employing simple reactions to the ground contact information, a more effective approach, which allows predictively avoiding obstacles, requires a model of the environment and a control algorithm that takes this model into account when planning footsteps and leg movements. This article addresses the issues of terrain perception and modeling and foothold selection in a walking robot. An integrated system is presented that allows a legged robot to traverse previously unseen, uneven terrain using only onboard perception, provided that a reasonable general path is known. An efficient method for real‐time building of a local elevation map from sparse two‐dimensional (2D) range measurements of a miniature 2D laser scanner is described. The terrain mapping module supports a foothold selection algorithm, which employs unsupervised learning to create an adaptive decision surface. The robot can learn from realistic simulations; therefore no a priori expert‐given rules or parameters are used. The usefulness of our approach is demonstrated in experiments with the six‐legged robot Messor. We discuss the lessons learned in field tests and the modifications to our system that turned out to be essential for successful operation under real‐world conditions. © 2011 Wiley Periodicals, Inc.     

面向离散地形的欠驱动双足机器人平衡控制方法

欠驱动双足机器人在行走中为保持自身的平衡, 双脚需要不间断运动. 但在仅有特定立足点的离散地形上很难实现调整后的落脚点, 从而导致欠驱动双足机器人在复杂环境中的适应能力下降. 提出了基于虚拟约束(Virtual constraint, VC)的变步长调节与控制方法, 根据欠驱动双足机器人当前状态与参考落脚点设计了非时变尺度缩放因子, 能够实时重构适应当前环境的步态轨迹; 同时构建了全身动力学模型, 采用反馈线性化的模型预测控制 (Model predictive control, MPC) 滚动优化产生力矩控制量, 实现准确的轨迹跟踪控制. 最终进行了欠驱动双足机器人的随机离散地形稳定行走的仿真实验, 验证了所提方法的有效性与鲁棒性.     

An adaptive locomotion controller for a hexapod robot: CPG,kinematics and force feedback

Insects can perform versatile locomotion behaviors such as multiple gaits, adapting to different terrains, fast escaping, etc. However, most of the existing bio-inspired legged robots do not possess such walking ability, especially when they walk on irregular terrains. To tackle this challenge, a central pattern generator （CPG）-based locomotion control methodology is proposed, integrated with a contact force feedback function. In this approach, multiple gaits are produced by the CFG module. After passing through a post-processing circuit and a delay-line, the control signal is fed into six trajectory generators to generate predefined feet trajectories for the six legs. Then, force feedback is employed to adjust these trajectories so as to adapt the robot to rough terrains. Finally the regulated trajectories are sent to inverse kinematics modules such that the position control instructions are generated to control the actuators. In both simulations and real robot experiments, we consistently show that the robot can perform sophisticated walking patterns. What is more, the robot can use the force feedback mechanism to deal with the irregularity in rough terrain. With this mechanism, the stability and adaptability of the robot are enhanced. In conclusion, the CPG-base control is an effective approach for legged robots and the force feedback approach is able to improve walking ability of the robots, especially when they walk on irregular terrains.     

Central pattern generator based reflexive control of quadruped walking robots using a recurrent neural network

This paper presents a novel Central Pattern Generator (CPG) model for controlling quadruped walking robots. The improvement of this model focuses on generating any desired waveforms along with accurate online modulation. In detail, a well-analyzed Recurrent Neural Network is used as the oscillators to generate simple harmonic periodic signals that exhibit limit cycle effects. Then, an approximate Fourier series is employed to transform those mentioned simple signals into arbitrary desired outputs under the phase constraints of several primary quadruped gaits. With comprehensive closed-form equations, the model also allows the user to modulate the waveform, the frequency and the phase constraint of the outputs online by directly setting the inner parameters without the need for any manual tuning. In addition, an associated controller is designed using leg coordination Cartesian position as the control state space based on which stiffness control is performed at sub-controller level. In addition, several reflex modules are embedded to transform the feedback of all sensors into the CPG space. This helps the CPG recognize external disturbances and utilize inner limit cycle effect to stabilize the robot motion. Finally, experiments with a real quadruped robot named AiDIN III performing several dynamic trotting tasks on several unknown natural terrains are presented to validate the effectiveness of the proposed CPG model and controller.     

Prior notice method of robotic arm motion for suppressing a threat to a human

The ability to develop a gait with one or more legs missing is an important issue for multi-legged robots used in demining applications. Accordingly, this paper presents a three-legged gait under the assumption that one leg of a quadruped walking robot is missing. After outlining a posture classification scheme for three-legged walking, the kick-and-swing gait is proposed as a basic and reasonable gait for three-legged walking and analyzed using a simple dynamic model. Minimum energy gait planning and an active shock-absorbing method are also investigated. The validity of the proposed gait is shown based on experiments using the quadruped walking robot TITAN VIII.     

Body Workspace of Quadruped Walking Robot and its Applicability in Legged Locomotion

This paper discusses on determination of the workspace of the body of a quadruped walking robot, called “body workspace”, and its applicability in legged locomotion. The body workspace represents the set of all valid body configurations for a next step by considering three constraints of a body position: existence of the inverse kinematic solutions, reach-ability of the next swing leg to the next desired foothold, and static equilibrium of the robot when the next swing leg is lifted. The space contains all the body positions that ensure the existence of inverse kinematic solutions, is calculated in the first. Then, a subspace inside the determined space that allows the robot to reach the next desired foothold is analyzed. Finally, the workspace is obtained by excluding all the positions inside the subspace that do not ensure the equilibrium of the robot when the next swing leg is lifted. Therefore, the workspace shows all possible solutions for choosing the next body configuration of a given static walking problem. It is significant in improving the robot’s performances since moving body takes an intrinsic role in static walking, besides swinging a leg. The algorithm runs fast in real-time because it is a pure geometric method. The body workspace of a quadruped walking robot is visualized to help the understanding of the algorithm. In addition, applications of using the body workspace in improving the robot’s ability are presented to show potential applicability of the workspace.