Fast approximate clearance evaluation for rovers with articulated suspension systems

We present a light‐weight body‐terrain clearance evaluation algorithm for the automated path planning of NASA's Mars 2020 rover. Extraterrestrial path planning is challenging due to the combination of terrain roughness and severe limitation in computational resources. Path planning on cluttered and/or uneven terrains requires repeated safety checks on all the candidate paths at a small interval. Predicting the future rover state requires simulating the vehicle settling on the terrain, which involves an inverse‐kinematics problem with iterative nonlinear optimization under geometric constraints. However, such expensive computation is intractable for slow spacecraft computers, such as RAD750, which is used by the Curiosity Mars rover and upcoming Mars 2020 rover. We propose the approximate clearance evaluation (ACE) algorithm, which obtains conservative bounds on vehicle clearance, attitude, and suspension angles without iterative computation. It obtains those bounds by estimating the lowest and highest heights that each wheel may reach given the underlying terrain, and calculating the worst‐case vehicle configuration associated with those extreme wheel heights. The bounds are guaranteed to be conservative, hence ensuring vehicle safety during autonomous navigation. ACE is planned to be used as part of the new onboard path planner of the Mars 2020 rover. This paper describes the algorithm in detail and validates our claim of conservatism and fast computation through experiments.     

Interaction Mechanics Model for Rigid Driving Wheels of Planetary Rovers Moving on Sandy Terrain with Consideration of Multiple Physical Effects

Predicting wheel‐terrain interaction with semiempirical models is of substantial importance for developing planetary wheeled mobile robots (rovers). Primarily geared toward the design of manned terrestrial vehicles, conventional terramechanics models do not provide the sufficient fidelity required for application on autonomous planetary rovers. To develop a high‐fidelity interaction mechanics model, in this study the physical effects of wheel lug, slip sinkage, wheel dimension, and load are analyzed based on experimental results, including wheel sinkage, drawbar pull, normal force, and moment, which are measured on a single‐wheel test bed. The mechanism of lug‐terrain interaction is investigated systematically to clarify the principle of increasing shear stress, conditions of forming successive shearing among adjacent lugs, and the influence on shear displacement of soil. A mathematical model for predicting the concentrated forces and torque of rigid wheels with lugs for planetary rovers moving on sandy terrain is derived by integrating the improved models of normal and shearing stress distributions. In addition to the wheel parameters, terrain parameters, and motion state variables, wheel‐terrain interaction parameters, such as the linear varying sinkage exponent, the soil displacement radius, and load effect parameters, were proposed and explicitly included in the model. In the single‐wheel experiments, the slip ratio was increased approximately from 0.05 to 0.6, and the relative errors of the predicted results using the proposed model are less than 10% for all the wheels when compared with the experimental data. The proposed model has been used in the simulation of a four‐wheeled rover, and its effectiveness is evaluated by comparing the simulation results with experimental results.     

Design and field testing of a rover with an actively articulated suspension system in a Mars analog terrain

This study presents the electromechanical design, the control approach, and the results of a field test campaign with the hybrid wheeled‐leg rover SherpaTT. The rover ranges in the 150 kg class and features an actively articulated suspension system comprising four legs with actively driven and steered wheels at each leg’s end. Five active degrees of freedom are present in each of the legs, resulting in 20 active degrees of freedom for the complete locomotion system. The control approach is based on force measurements at each wheel mounting point and roll–pitch measurements of the rover’s main body, allowing active adaption to sloping terrain, active shifting of the center of gravity within the rover’s support polygon, active roll–pitch influencing, and body‐ground clearance control. Exteroceptive sensors such as camera or laser range finder are not required for ground adaption. A purely reactive approach is used, rendering a planning algorithm for stability control or force distribution unnecessary and thus simplifying the control efforts. The control approach was tested within a 4‐week field deployment in the desert of Utah. The results presented in this paper substantiate the feasibility of the chosen approach: The main power requirement for locomotion is from the drive system, active adaption only plays a minor role in power consumption. Active force distribution between the wheels is successful in different footprints and terrain types and is not influenced by controlling the body’s roll–pitch angle in parallel to the force control. Slope‐climbing capabilities of the system were successfully tested in slopes of up to 28° inclination, covered with loose soil and duricrust. The main contribution of this study is the experimental validation of the actively articulated suspension of SherpaTT in conjunction with a reactive control approach. Consequently, hardware and software design as well as experimentation are part of this study.     

月球车驱动轮爬坡性能的影响因素研究

研究了驱动轮的滑转率、结构参数和载荷对月球车爬坡性能的影响。针对月表复杂路况下车辆通过性较差问题,为提高月球车爬坡性能,基于车辆地面力学中土壤的承压和剪切特性理论,建立了刚性驱动轮与月面斜坡松软月壤间的相互作用模型。通过车轮实例对月球车爬坡性能进行预测和分析。实验结果表明,增大驱动轮的滑转率、半径、宽度、轮刺高度和减小载荷能够增强月球车爬坡能力和提高车轮驱动效率,但随着爬坡能力的增强,车轮驱动效率呈现先增大后减小的趋势。研究结果为月球车轮结构设计以及控制策略的研究提供了参考。     

Mars Science Laboratory Curiosity Rover Megaripple Crossings up to Sol 710 in Gale Crater

After landing in Gale Crater on August 6, 2012, the Mars Science Laboratory Curiosity rover traveled across regolith‐covered, rock‐strewn plains that transitioned into terrains that have been variably eroded, with valleys partially filled with windblown sands, and intervening plateaus capped by well‐cemented sandstones that have been fractured and shaped by wind into outcrops with numerous sharp rock surfaces. Wheel punctures and tears caused by sharp rocks while traversing the plateaus led to directing the rover to traverse in valleys where sands would cushion wheel loads. This required driving across a megaripple (windblown, sand‐sized deposit covered by coarser grains) that straddles a narrow gap and several extensive megaripple deposits that accumulated in low portions of valleys. Traverses across megaripple deposits led to mobility difficulties, with sinkage values up to approximately 30% of the 0.50 m wheel diameter, resultant high compaction resistances, and rover‐based slip up to 77%. Analysis of imaging and engineering data collected during traverses across megaripples for the first 710 sols (Mars days) of the mission, laboratory‐based single‐wheel soil experiments, full‐scale rover tests at the Dumont Dunes, Mojave Desert, California, and numerical simulations show that a combination of material properties and megaripple geometries explain the high wheel sinkage and slip events. Extensive megaripple deposits have subsequently been avoided and instead traverses have been implemented across terrains covered with regolith or thin windblown sand covers and megaripples separated by bedrock exposures.     

Dynamic path tracking control of a vehicle on slippery terrain

This paper deals with accuracy and reliability for the path tracking control of a four wheel mobile robot with a double-steering system when moving at high dynamics on a slippery surface. An extended kinematic model of the robot is developed considering the effects of wheel–ground skidding. This bicycle type model is augmented to form a dynamic model that considers an actuation of the four wheels. Based on the extended kinematic model, an adaptive and predictive controller for the path tracking is developed to drive the wheels front and rear steering angles. The resulting control law is combined with a stabilization algorithm of the yaw motion which modulates the actuation torque of each four wheels, on the basis of the robot dynamic model. The global control architecture is experimentally evaluated on a wet grass slippery terrain, with speeds up to 7 m/s. Experimental results demonstrate enhancement of tracking performances in terms of stability and accuracy relative to the kinematic control.     

Modeling of flexible metal wheel for pressurized lunar rover and traction performance prediction

The pressurized lunar rover has become one of the most important equipment in lunar exploration and resource utilization missions. On the terrain of soft lunar regolith, the rover wheels are easy to slip, sink, or even fail to move. To improve the traction performance of the rover on soft lunar soil, it is necessary to study the interaction between the wheels and the lunar soil. The deformation of the flexible wheel provides a larger contact area, which results in greater tractive force. Moreover, flexible wheels have better comfort and stability than rigid wheels, which are needed for manned rovers. However, there are few studies on the wheel soil interaction model of the heavy flexible wheel for the pressurized lunar rover. In this paper, a metal flexible wheel soil interaction model for pressurized lunar rovers was established, and the traction performance of the flexible wheel was predicted by using this model. Then, the accuracy of the wheel soil interaction model was verified by the soil bin test. The experimental results showed that the average error between the theoretical value of sinkage and the experimental value was 13.9%, and the average error between the theoretical and experimental value of drawbar pull was 11.5%, indicating that the model has high prediction accuracy. The new model can be used to predict the traction performance of flexible wheels and the experimental results can provide a reference for the flexible wheel design lunar rovers.     

Self‐reliant rovers for increased mission productivity

Achieving consistently high levels of productivity has been a challenge for Mars surface missions. While the rovers have made major discoveries and dramatically increased our understanding of Mars, they require a great deal of interaction from the operations teams, and achieving mission objectives can take longer than anticipated when productivity is paced by the ground teams' ability to react. We have conducted a project to explore technologies and techniques for creating self‐reliant rovers (SRR): rovers that are able to maintain high levels of productivity with reduced reliance on ground interactions. This paper describes the design of SRR and a prototype implementation that we deployed on a research rover. We evaluated the system by conducting a simulated campaign in which members of the Mars Science Laboratory (Curiosity rover) science team used our rover to explore a geographical region. The evaluation demonstrated the system's ability to maintain high levels of productivity with limited communication with operators.     

The evolution of the curiosity rover sampling chain

The Mars Science Laboratory (MSL) Curiosity rover landed in Gale crater in August of 2012 on its mission to explore Mt. Sharp as the first planetary rover to collect and analyze rock and regolith samples. On this new mission, sampling operations were conceived to be executed serially and in situ, on a “sample chain” along which sample would be collected, then processed, then delivered to sample analysis instruments, analyzed there, and then discarded so the chain could be repeated. This paper describes the evolution of this relatively simple chain into a richer sampling network, responding to science and engineering desires that came into focus only as the mission matured, scientific discoveries were made, and anomalies were encountered. The rover flight and ground system architectures retained significant heritage from past missions, while extending capabilities in anticipation of the need for adaptation. As evolution occurred, the architecture permitted nimble extension of sampling behavior without time‐consuming flight software updates or significant impact to daily operations. This paper presents the major components of this architecture and discusses some of the results of successful adaptation across thousands of Sols of Mars operations.     

基于滑转率的六轮纵列式月球车驱动控制研究

基于车轮滑转率和车轮地面力学,研究了月球车在松软月面行驶时的车轮过度下陷问题.将 月球车车轮下陷和车轮—土壤作用力表达为车轮滑转率的函数,结合车辆地面力学理论并考 虑纵列式车轮多通过性土壤参数的修正,建立了月球车的动力学模型.判断车轮是否发生过 度下陷的标准为土壤所提供给驱动轮的土壤推力能否克服土壤对车轮的阻力.利用建立的动 力学模型,计算出能够保证车轮不会过度下陷的期望滑转率.考虑到月球车动力学系统的非 线性和不确定性,设计了以车轮滑转率为状态变量的滑模驱动控制器.仿真结果表明,采用 该控制器可以较快地跟踪期望滑转率,避免车轮的过度滑转下陷,保证月球车能够在软质路 面上正常行驶.     

Attitude-based dynamic and kinematic models for wheels of mobile robot on deformable slope

Deformable slope is a type of terrain that wheeled mobile robots (WMRs) and ground unmanned vehicles (GUVs) may have to traverse to accomplish their mission tasks. However, the associated terramechanics for wheels with arbitrary posture is rarely studied. In this paper, based on wheel attitude, dynamics of the wheel–terrain interaction for a rigid wheel on deformable slope is investigated. Through introducing the angular geometry of wheel attitude into terramechanics theory, a generalized dynamic model is developed, involving two inclination angles of slope and three attitude angles of wheel steering axis. Two representative cases are studied: the wheel runs straight forward and perpendicular to the slope, and the wheel is in a steering maneuver with an inclined steering axis. A generalized kinematic model for wheel–terrain contact point and wheel center is also provided, which analytically explicates that trajectory of wheel motion is coupled with wheel attitude while driven by angular rates. The proposed attitude-based models are valid for arbitrary wheel–terrain geometry and can lead to control purpose directly. Effectiveness of the models is confirmed by simulating the influences from attitude to wheel mechanics and motion.     

Long‐range rover localization by matching LIDAR scans to orbital elevation maps

Current rover localization techniques such as visual odometry have proven to be very effective on short‐ to medium‐length traverses (e.g., up to a few kilometers). This paper deals with the problem of long‐range rover localization (e.g., 10 km and up) by developing an algorithm named MOGA (Multi‐frame Odometry‐compensated Global Alignment). This algorithm is designed to globally localize a rover by matching features detected from a three‐dimensional (3D) orbital elevation map to features from rover‐based, 3D LIDAR scans. The accuracy and efficiency of MOGA are enhanced with visual odometry and inclinometer/sun‐sensor orientation measurements. The methodology was tested with real data, including 37 LIDAR scans of terrain from a Mars–Moon analog site on Devon Island, Nunavut. When a scan contained a sufficient number of good topographic features, localization produced position errors of no more than 100 m, of which most were less than 50 m and some even as low as a few meters. Results were compared to and shown to outperform VIPER, a competing global localization algorithm that was given the same initial conditions as MOGA. On a 10‐km traverse, MOGA's localization estimates were shown to significantly outperform visual odometry estimates. This paper shows how the developed algorithm can be used to accurately and autonomously localize a rover over long‐range traverses. © 2010 Wiley Periodicals, Inc.     

可翻转星球探测车的原型设计

给出了一种四面都可着地行驶、不怕翻转的星球探测车原型设计方案,着重解决了探测车翻转后失效的问题．在该方案中,采用了特殊的45度轮架机构,用八轮实现了每个侧面都有四轮着地行驶;研制了新型姿态传感器,实现了探测车的姿态判断;设计了太阳能储能供电装置,能保持太阳能板始终在车的上方,从而为探测车有效提供能源．实验显示这种探测车达到了预期的功能,在星球探测、人员搜救、军事侦察等领域有一定的研究应用价值．     

Trafficability Assessment of Deformable Terrain through Hybrid Wheel‐Leg Sinkage Detection

Off‐road ground mobile robots are widely used in diverse applications, both in terrestrial and planetary environments. They provide an efficient alternative, with lower risk and cost, to explore or to transport materials through hazardous or challenging terrain. However, nongeometric hazards that cannot be detected remotely pose a serious threat to the mobility of such robots. A prominent example of the negative effects these hazards can have is found on planetary rover exploration missions. They can cause a serious degradation of mission performance at best and complete immobilization and mission failure at worst. To tackle this issue, the work presented in this paper investigates the novel application of an existing enhanced‐mobility locomotion concept, a hybrid wheel‐leg equipped by a lightweight micro‐rover, for in situ characterization of deformable terrain and online detection of nongeometric hazards. This is achieved by combining an improved vision‐based approach and a new ranging‐based approach to wheel‐leg sinkage detection. In addition, the paper proposes an empirical model, and a parametric generalization, to predict terrain trafficability based on wheel‐leg sinkage and a well‐established semiempirical terramechanics model. The robustness and accuracy of the sinkage detection methods implemented are tested in a variety of conditions, both in the laboratory and in the field, using a single wheel‐leg test bed. The sinkage‐trafficability model is developed based on experimental data using this test bed and then validated onboard a fully mobile robot through experimentation on a range of dry frictional soils that covers a wide spectrum of macroscopic physical characteristics.     

Improved Rover State Estimation in Challenging Terrain

Given ambitious mission objectives and long delay times between command-uplink/data-downlink sessions, increased autonomy is required for planetary rovers. Specifically, NASA's planned 2003 and 2005 Mars rover missions must incorporate increased autonomy if their desired mission goals are to be realized. Increased autonomy, including autonomous path planning and navigation to user designated goals, relies on good quality estimates of the rover's state, e.g., its position and orientation relative to some initial reference frame. The challenging terrain over which the rover will necessarily traverse tends to seriously degrade a dead-reckoned state estimate, given severe wheel slip and/or interaction with obstacles. In this paper, we present the implementation of a complete rover navigation system. First, the system is able to adaptively construct semi-sparse terrain maps based on the current ground texture and distances to possible nearby obstacles. Second, the rover is able to match successively constructed terrain maps to obtain a vision-based state estimate which can then be fused with wheel odometry to obtain a much improved state estimate. Finally the rover makes use of this state estimate to perform autonomous real-time path planning and navigation to user designated goals. Reactive obstacle avoidance is also implemented for roaming in an environment in the absence of a user designated goal. The system is demonstrated in soft soil and relatively dense rock fields, achieving state estimates that are significantly improved with respect to dead reckoning alone (e.g., 0.38 m mean absolute error vs. 1.34 m), and successfully navigating in multiple trials to user designated goals.     

Independent traction control for uneven terrain using stick-slip phenomenon: application to a stair climbing robot

Mobile robots are being developed for building inspection and security, military reconnaissance, and planetary exploration. In such applications, the robot is expected to encounter rough terrain. In rough terrain, it is important for mobile robots to maintain adequate traction as excessive wheel slip causes the robot to lose mobility or even be trapped. This paper proposes a traction control algorithm that can be independently implemented to each wheel without requiring extra sensors and devices compared with standard velocity control methods. The algorithm estimates the stick-slip of the wheels based on estimation of angular acceleration. Thus, the traction force induced by torque of wheel converses between the maximum static friction and kinetic friction. Simulations and experiments are performed to validate the algorithm. The proposed traction control algorithm yielded a 40.5% reduction of total slip distance and 25.6% reduction of power consumption compared with the standard velocity control method. Furthermore, the algorithm does not require a complex wheel-soil interaction model or optimization of robot kinematics.     

Slip-compensated path following for planetary exploration rovers

A system that enables continuous slip compensation for a Mars rover has been designed, implemented and field-tested. This system is composed of several components that allow the rover to accurately and continuously follow a designated path, compensate for slippage and reach intended goals in high-slip environments. These components include visual odometry, vehicle kinematics, a Kalman filter pose estimator and a slip-compensated path follower. Visual odometry tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs. The kinematics for a rocker–bogie suspension system estimates vehicle motion by measuring wheel rates, and rocker, bogie and steering angles. The Kalman filter processes measurements from an inertial measurement unit and visual odometry. The filter estimate is then compared to the kinematic estimate to determine whether slippage has occurred, taking into account estimate uncertainties. If slippage is detected, the slip vector is calculated by differencing the current Kalman filter estimate from the kinematic estimate. This slip vector is then used to determine the necessary wheel velocities and steering angles to compensate for slip and follow the desired path.     

Control of Robotic Vehicles with Actively Articulated Suspensions in Rough Terrain

Future robotic vehicles will perform challenging tasks in rough terrain, such as planetary exploration and military missions. Rovers with actively articulated suspensions can improve rough-terrain mobility by repositioning their center of mass. This paper presents a method to control actively articulated suspensions to enhance rover tipover stability. A stability metric is defined using a quasi-static model, and optimized on-line. The method relies on estimation of wheel-terrain contact angles. An algorithm for estimating wheel-terrain contact angles from simple on-board sensors is developed. Simulation and experimental results are presented for the Jet Propulsion Laboratory Sample Return Rover that show the control method yields substantially improved stability in rough-terrain.     

星球车松软星壤的轮腿式探测系统:Ⅱ-感知车轮

为增强星球车松软星壤的穿越通过能力,提出了轮壤交互接触信息的感知车轮设计。该车轮是一种星球车的前置轮腿式探测系统(WOLS)的关键部分,可实现动态轮壤交互的关键量测量(轮壤作用力/力矩、轮壤接触角和车轮沉陷量)。研究分析了轮壤力学的关键测量参量及其分组,完成了感知车轮的硬件设计和集成,提出了待测参数的在线测量模型和方法,通过标定校准和实车测试验证了该感知车轮的性能。     

电机故障对月球车驱动轮牵引性能的影响

月球车是一种在外太空极端恶劣环境下长时间自主运行、不可维修的轮式移动机器人,为准确预测车轮驱动电机故障运行时的牵引性能对于月球车的可靠性有重要意义。为确保月球车顺利完成任务,建立了电机正常运行时的电磁场仿真模型,在模型基础上针对开关管短路、开关管开路、霍尔位置信号恒值和绕组开路等分别建立了故障仿真模型,通过仿真确定了能够识别各种故障的特征波形,并绘制了电机的机械特性曲线。应用车辆地面力学理论对比分析了电机正常与故障运行时驱动轮牵引性能的变化。研究结果表明,当电机发生各种故障后,驱动轮的牵引性能均有不同程度的下降。可为带障运行条件下的多轮协调控制策略的制定提供了理论依据。