State estimation and traversability map construction method of a quadruped robot on soft uneven terrain

Quadruped robots show excellent application prospects in complex environment detection and rescue. At present, scholars mainly focus on quadruped walking in rigid environments. However, quadruped robots often need to pass through uneven and soft unconstructed terrains, prone to slip and impact. The mismatch between the planned foothold position and the real one resulting from environmental uncertainties makes the robot unstable. In this paper, the state estimation and traversability map construction methods are proposed for quadruped robots to achieve stable walking in an unstructured environment, especially on soft terrains. First, the Error-state Kalman Filter (ErKF) is extended by optimizing the leg odometry information to get an accurate robot state, especially in soft, uneven terrain. The ErKF method fuses the sensor data from the inertial measurement unit, laser, camera, and leg odometry. The leg odometry is optimized by considering the foot slippage, which easily occurs in soft uneven terrains. Then, the unstructured environment is parameterized and modeled by the terrain inclination, roughness, height, and stiffness. A traversability map, which is essential for robot path and foothold planning in autonomous movement, is constructed with the above parameters. Finally, the proposed method is verified by simulation and experiments. The results show that the quadruped robot can walk stably on different soft and uneven terrains.     

Path planning for a quadruped robot: an artificial field approach

In this paper, we consider the problem of planning a feasible path for a quadruped walking robot in an environment of obstacles. In conventional path-planning problems, the main focus is merely collision avoidance with obstacles since a wheeled robot is involved. However, in the case of a legged robot, both collision avoidance and crossing over obstacles must be taken into account in the process of path planning. Furthermore, the constraints of the gait should be considered to guarantee the feasibility of a planned path. To resolve this complicated problem in a systematic way, a new concept of an artificial thermal field is proposed. Specifically, with the assumption that a robot walks with a periodic crab gait, a robot and obstacles in a three-dimensional (3D) space are projected on a 2D plane. Next, the 2D obstacles are transformed into the configuration space of a quadruped robot. A feasible path is finally sought in an artificial thermal field which is constructed numerically on the discretized configuration space. To verify the efficacy of the proposed approach, three notable simulation results are provided.     

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.     

连续电驱动四足机器人腿部机构设计与分析

提出了一种四足机器人腿部的连续电驱动（即电机整周转动驱动腿部实现摆转跨步动作）方案,设计了一种具有由切比雪夫机构、五杆机构组成的2自由度双曲柄复合连杆机构的机器人腿部结构．分析了动物的足端轨迹特性,采用轨迹圆滑、无突变、导数连续的椭圆曲线规划了机器人足端运动轨迹．以规划的足端轨迹再现为优化目标,采用遗传算法与fmincon函数内点法计算得到了腿部机构杆长的最佳尺寸．在此基础上,建立了机器人仿真模型,通过Adams仿真分析了机器人腿部机构的足端运动特性,并研制了腿部结构性能测试平台．完成了单腿足端运动轨迹跟踪实验,验证了腿部结构设计方案的可行性．     

A modular approach to intelligent control of a simulated jointedleg

Each module handles one phase of the running stride. A self-organizing fuzzy takeoff controller controls the size and angular momentum of the stride. A neural network based ballistic controller controls the movement of the airborne leg; and a similar landing controller repositions the leg for takeoff of the next stride     

基于扩展雅可比矩阵的冗余液压驱动四足机器人运动控制

针对冗余液压驱动四足机器人运动学逆解问题,提出一种基于扩展雅可比矩阵的冗余液压驱动四足机器人运动控制方法.该方法既能解决冗余自由度带来的逆解多解问题,还能使机器人足端入地角度满足摩擦锥要求避免足端滑动.首先,规划机器人足端轨迹得到机器人足端速度,在分析机器人足端入地角度对机器人运动性能影响的基础上,结合机器人腿部结构几...     

一种多模型融合的仿猎豹四足机器人复杂运动控制方法

针对具有2自由度主动脊柱关节的仿猎豹四足机器人,基于任务分解思想和生物神经系统机理,提出多模型融合的控制方法。该方法以弹簧负载倒立摆模型实现单腿跳跃控制,通过中枢模式发生器（CPG）实现4条腿之间以及脊柱―腿之间的协调控制,利用虚拟模型控制实现机器人与环境交互,采用基于CPG输出的有限状态机来融合3个控制模型,构建仿猎豹四足机器人的多模型分层运动控制器。参考猎豹脊柱运动特征,设计了机器人脊柱关节运动模式,给出脊柱与腿的协调控制策略。最后,在Webots仿真环境中搭建了仿猎豹四足机器人虚拟样机,实现了不同步态下的脊柱―腿的协调控制、在崎岖地形上稳定奔跑,以及平滑的对角―疾驰―对角步态转换,仿真结果验证了所提出的多模型融合的四足机器人运动控制方法的有效性。     

滑跑无人机起降过程动力学特性分析及性能底数评估

在备战打仗大环境下,为了给装备试验考核提供技术参考,针对滑跑起降无人机起降阶段机身-起落架-地面之间复杂的动态特性,本文建立了飞机-起落架-跑道的系统动力学仿真模型及动力学方程,分别采用多尺度法和有限元分析法研究了其在不同气动载荷、重力以及作动筒载荷耦合作用下的系统动力学特性,并对可靠性和安全性进行了仿真分析.结果表明,不同降落速度对起落架-地面系统的动力学行为有较大的影响；起落架系统强度、刚度和安全特性满足相关指标.通过滑跑起降无人机动态安全特性以及在飞行作战中的极限疲劳寿命分析,为后续武器装备的考核以及性能底数评估提供了技术参考.     

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.     

Fault-tolerant locomotion of the hexapod robot

In this paper, we propose a scheme for fault detection and tolerance of the hexapod robot locomotion on even terrain. The fault stability margin is defined to represent potential stability which a gait can have in case a sudden fault event occurs to one leg. Based on this, the fault-tolerant quadruped periodic gaits of the hexapod walking over perfectly even terrain are derived. It is demonstrated that the derived quadruped gait is the optimal one the hexapod can have maintaining fault stability margin nonnegative and a geometric condition should be satisfied for the optimal locomotion. By this scheme, when one leg is in failure, the hexapod robot has the modified tripod gait to continue the optimal locomotion.     

Adaptive dynamic walking of a quadruped robot using a neural system model

We are trying to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model. In this paper, we integrate several reflexes, such as a stretch reflex, a vestibulospinal reflex and extensor/flexor reflexes, into a central pattern generator (CPG). We try to realize adaptive walking up and down a slope of 12°, walking over an obstacle 3 cm in height, and walking on terrain undulation consisting of bumps 3 cm in height with fixed parameters of CPGs and reflexes. The success in walking on such irregular terrain in spite of stumbling and landing on obstacles shows that the control method using a neural system model proposed in this study has the ability for autonomous adaptation to unknown irregular terrain. In order to clarify the role of a CPG, we investigate the relation between parameters of a CPG and the mechanical system by simulations and experiments. CPGs can generate stable walking suitable for the mechanical system by receiving inhibitory input as sensory feedback and generate adaptive walking on irregular terrain by receiving excitatory input as sensory feedback. MPEG footage of these experiments can be seen at: http://www.kimura.is.uec.ac.jp.     

Steerable miniature jumping robot

Jumping is used in nature by many small animals to locomote in cluttered environments or in rough terrain. It offers small systems the benefit of overcoming relatively large obstacles at a low energetic cost. In order to be able to perform repetitive jumps in a given direction, it is important to be able to upright after landing, steer and jump again. In this article, we review and evaluate the uprighting and steering principles of existing jumping robots and present a novel spherical robot with a mass of 14 g and a size of 18 cm that can jump up to 62 cm at a take-off angle of 75°, recover passively after landing, orient itself, and jump again. We describe its design details and fabrication methods, characterize its jumping performance, and demonstrate the remote controlled prototype repetitively moving over an obstacle course where it has to climb stairs and go through a window. (See videos 1–4 in the electronic supplementary material.)     

基于Klann连杆的球腿复合机器人的设计与研究

结合球形和四足机器人两者优势,创新性地提出一种能适应多重作业环境的球腿复合移动机器人．在滚动模式下,对其进行直线滚动和侧滚转向分析,验证机器人转向的可行性．在四足模式下,以复数矢量法求得机器人足端坐标,并用Matlab绘制的足端轨迹曲线与Adams仿真曲线对比,验证了理论的正确性．以抬腿高度作为目标函数,由非线性规划算法求得足端轨迹最优解．采用质心投影法分析了机器人四足行走时的稳定性．建立仿真模型对机器人的四足直行、四足转向、四足爬坡和球体侧滚等运动模式进行仿真试验．同时,制作一台样机,验证了该机器人方案设计及各运动模式的可行性．     

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.     

LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR CONTROL

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.     

基于弹簧负载倒立摆模型的仿袋鼠机器人稳定跳跃控制

仿生跳跃机器人具备很强的越障和环境适应能力,但是由于机器人运动过程中较短的可控时间以及腾空阶段运动的不确定性,运动的稳定性对于仿生跳跃机器人至关重要.本文对仿袋鼠机器人跳跃运动过程中的稳定跳跃控制问题进行了研究.首先采用双质量弹簧负载倒立摆模型(spring-loaded inverted pendulum,SLIP)模型对袋鼠机器人的结构进行简化,建立了机器人系统的动力学模型,并对机器人的运动过程以及着地相与腾空相的切换条件进行了分析.然后采用解耦控制的思想,将SLIP模型的运动控制分解为水平速度控制和跳跃高度控制两个方面,分别通过控制着地角度实现对水平运动速度的控制,通过能量补偿实现对跳跃高度的控制.最后在ADAMS仿真环境中建立机器人模型并进行了机器人运动仿真实验.实验结果表明,本文提出的方法可以实现仿袋鼠机器人稳定的周期性跳跃运动.     

Generating continuous free crab gaits for quadruped robots on irregular terrain

This paper presents a method for generating free gaits for quadruped robots capable of performing statically stable, omnidirectional locomotion on irregular terrain containing forbidden areas. The rule-based deliberative algorithm can generate flexible sequences of leg transferences while maintaining constant vehicle speed. The foothold planning method is compatible with the use of these flexible leg sequences, and is designed to maintain a minimum absolute stability margin despite the terrain height uncertainty. The integration of exteroceptive terrain profile data has been considered to improve adaptability. Experimental results are presented to show the gait's efficiency in adapting to an irregular terrain containing forbidden areas.     

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.     

基于深度强化学习的三维路径规划算法

合理的路线选择是智能体三维路径规划研究领域的难点。现有路径规划方法存在不能很好地适应未知地形,避障形式单一等问题。针对这些问题,提出了一种基于LSTM-PPO的智能体三维路径规划算法。利用虚拟射线探测仿真环境,并将收集到的状态空间和动作状态引入长短时记忆网络。通过额外的奖惩函数和好奇心驱动让智能体学会跳跃通过低矮障碍物,避开大型障碍物。利用PPO算法的截断项机制使得规划策略更新的幅度更加优化。实验结果表明,该算法是可行的,能够更加智能合理地选择路线,很好地适应存在多样障碍物的未知环境。