Methods for Wheel Slip and Sinkage Estimation in Mobile Robots

Future outdoor mobile robots will have to explore larger and larger areas, performing difficult tasks, while preserving, at the same time, their safety. This will primarily require advanced sensing and perception capabilities. Video sensors supply contact-free, precise measurements and are flexible devices that can be easily integrated with multi-sensor robotic platforms. Hence, they represent a potential answer to the need of new and improved perception capabilities for autonomous vehicles. One of the main applications of vision in mobile robotics is localization. For mobile robots operating on rough terrain, conventional dead reckoning techniques are not well suited, since wheel slipping, sinkage, and sensor drift may cause localization errors that accumulate without bound during the vehicle’s travel. Conversely, video sensors are exteroceptive devices, that is, they acquire information from the robot’s environment; therefore, vision-based motion estimates are independent of the knowledge of terrain properties and wheel-terrain interaction. Indeed, like dead reckoning, vision could lead to accumulation of errors; however, it has been proved that, compared to dead reckoning, it allows more accurate results and can be considered as a promising solution to the problem of robust robot positioning in high-slip environments. As a consequence, in the last few years, several localization methods using vision have been developed. Among them, visual odometry algorithms, based on the tracking of visual features over subsequent images, have been proved particularly effective. Accurate and reliable methods to sense slippage and sinkage are also desirable, since these effects compromise the vehicle’s traction performance, energy consumption and lead to gradual deviation of the robot from the intended path, possibly resulting in large drift and poor results of localization and control systems. For example, the use of conventional dead-reckoning technique is largely compromised, since it is based on the assumption that wheel revolutions can be translated into correspondent linear displacements. Thus, if one wheel slips, then the associated encoder will register revolutions even though these revolutions do not correspond to a linear displacement of the wheel. Conversely, if one wheel skids, fewer encoder pulses will be counted. Slippage and sinkage measurements are also valuable for terrain identification according to the classical terramechanics theory. This chapter investigates vision-based onboard technology to improve mobility of robots on natural terrain. A visual odometry algorithm and two methods for online measurement of vehicle slip angle and wheel sinkage, respectively, are discussed. Tests results are presented showing the performance of the proposed approaches using an all-terrain rover moving across uneven terrain

Learning to visually predict terrain properties for planetary rovers

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 174-180).For future planetary exploration missions, improvements in autonomous rover mobility have the potential to increase scientific data return by providing safe access to geologically interesting sites that lie in rugged terrain, far from landing areas. This thesis presents an algorithmic framework designed to improve rover-based terrain sensing, a critical component of any autonomous mobility system operating in rough terrain. Specifically, this thesis addresses the problem of predicting the mechanical properties of distant terrain. A self-supervised learning framework is proposed that enables a robotic system to learn predictions of mechanical properties of distant terrain, based on measurements of mechanical properties of similar terrain that has been previously traversed. The proposed framework relies on three distinct algorithms. A mechanical terrain characterization algorithm is proposed that computes upper and lower bounds on the net traction force available at a patch of terrain, via a constrained optimization framework. Both model-based and sensor-based constraints are employed. A terrain classification method is proposed that exploits features from proprioceptive sensor data, and employs either a supervised support vector machine (SVM) or unsupervised k-means classifier to assign class labels to terrain patches that the rover has traversed. A second terrain classification method is proposed that exploits features from exteroceptive sensor data (e.g. color and texture), and is automatically trained in a self-supervised manner, based on the outputs of the proprioceptive terrain classifier.(cont.) The algorithm includes a method for distinguishing novel terrain from previously observed terrain. The outputs of these three algorithms are merged to yield a map of the surrounding terrain that is annotated with the expected achievable net traction force. Such a map would be useful for path planning purposes. The algorithms proposed in this thesis have been experimentally validated in an outdoor, Mars-analog environment. The proprioceptive terrain classifier demonstrated 92% accuracy in labeling three distinct terrain classes. The exteroceptive terrain classifier that relies on self-supervised training was shown to be approximately as accurate as a similar, human-supervised classifier, with both achieving 94% correct classification rates on identical data sets. The algorithm for detection of novel terrain demonstrated 89% accuracy in detecting novel terrain in this same environment. In laboratory tests, the mechanical terrain characterization algorithm predicted the lower bound of the net available traction force with an average margin of 21% of the wheel load.by Christopher A. Brooks.Ph.D

Terrain physical properties derived from orbital data and the first 360 sols of Mars Science Laboratory Curiosity rover observations in Gale Crater

Physical properties of terrains encountered by the Curiosity rover during the first 360 sols of operations have been inferred from analysis of the scour zones produced by Sky Crane Landing System engine plumes, wheel touch down dynamics, pits produced by Chemical Camera (ChemCam) laser shots, rover wheel traverses over rocks, the extent of sinkage into soils, and the magnitude and sign of rover‐based slippage during drives. Results have been integrated with morphologic, mineralogic, and thermophysical properties derived from orbital data, and Curiosity‐based measurements, to understand the nature and origin of physical properties of traversed terrains. The hummocky plains (HP) landing site and traverse locations consist of moderately to well‐consolidated bedrock of alluvial origin variably covered by slightly cohesive, hard‐packed basaltic sand and dust, with both embedded and surface‐strewn rock clasts. Rock clasts have been added through local bedrock weathering and impact ejecta emplacement and form a pavement‐like surface in which only small clasts (<5 to 10 cm wide) have been pressed into the soil during wheel passages. The bedded fractured (BF) unit, site of Curiosity's first drilling activity, exposes several alluvial‐lacustrine bedrock units with little to no soil cover and varying degrees of lithification. Small wheel sinkage values (<1 cm) for both HP and BF surfaces demonstrate that compaction resistance countering driven‐wheel thrust has been minimal and that rover slippage while traversing across horizontal surfaces or going uphill, and skid going downhill, have been dominated by terrain tilts and wheel‐surface material shear modulus values

Characterization of Fillite as a Planetary Soil Simulant in Support of Rover Mobility Assessment in High-Sinkage/High-Slip Environments

This thesis presents the results of a research program characterizing a soil simulant called Fillite, which is composed of alumino-silicate hollow microspheres harvested from the pulverized fuel ash of coal-fired power plants. Fillite is available in large quantities at a reasonable cost and it is chemically inert. Fillite has been selected by the National Aeronautics and Space Administration (NASA) Glenn Research Center to simulate high-sinkage/high-slip environment in a large test bed such as the ones encountered by the Spirit rover on Mars in 2009 when it became entrapped in a pocket of soft, loose regolith on Mars. The terms high-sinkage and high-slip used here describe the interaction of soils with typical rover wheels. High-sinkage refers to a wheel sinking with little to no applied force while high-slip refers to a spinning wheel with minimal traction. Standard material properties (density, specific gravity, compression index, Young\u27s modulus, and Poisson\u27s ratio) of Fillite were determined from a series of laboratory tests conducted in general accordance with ASTM standards. Tests were also performed to determine some less standard material properties of Fillite such as the small strain shear wave velocity, maximum shear modulus, and several pressure-sinkage parameters for use in pressure-sinkage models. The experiments include an extensive series of triaxial compression tests, bender element tests, and normal and shear bevameter tests. The unit weight of Fillite on Earth ranges between 3.9 and 4.8 kN/m3, which is similar to that of Martian regolith (about 3.7 - 5.6 kN/m3) on Mars and close to the range of the unit weight of lunar regolith (about 1.4 - 2.9 kN/m3) on the Moon. The data presented here support that Fillite has many physical and mechanical properties that are similar to what is known about Martian regolith. These properties are also comparable to lunar regolith. Fillite is quite dilatant; its peak and critical angles of internal friction are smaller than those of most other simulants. Smaller shear strength, coupled with much smaller bulk unit weight as compared to other simulants, results in smaller bearing and shearing resistances allowing for better simulation of the intended high-sinkage, high-slip behavior for rover mobility studies. The results of the normal bevameter tests were used to determine parameters for two models available in the literature - the Bekker model and the New Model of Mobility (N2M) model. These parameters were then used to predict the sinkage of a Spirit rover wheel if the rover were to be used on Fillite. The predicted sinkage of a Spirit rover wheel in Fillite was 84% of the wheel diameter, which was within the observed sinkage of 50 to 90% of the wheel diameter of the Spirit rover on Mars. Shear bevameter tests were also performed on Fillite to assess the shear stresses and shear deformations imparted by wheels under torsional loads. The results compared well to the estimated shear stresses and deformations of Martian soil caused by the wheels of the Spirit rover. When compared to other simulants (e.g. GRC-1), the pressure-sinkage and shear stress-shear deformation behaviors of Fillite confirm that Fillite is more suitable for high-sinkage and high-slip rover studies than other typical simulants derived from natural terrestrial soils and rocks

Opportunity Mars Rover mission: Overview and selected results from Purgatory ripple to traverses to Endeavour crater

Opportunity has been traversing the Meridiani plains since 25 January 2004 (sol 1), acquiring numerous observations of the atmosphere, soils, and rocks. This paper provides an overview of key discoveries between sols 511 and 2300, complementing earlier papers covering results from the initial phases of the mission. Key new results include (1) atmospheric argon measurements that demonstrate the importance of atmospheric transport to and from the winter carbon dioxide polar ice caps; (2) observations showing that aeolian ripples covering the plains were generated by easterly winds during an epoch with enhanced Hadley cell circulation; (3) the discovery and characterization of cobbles and boulders that include iron and stony-iron meteorites and Martian impact ejecta; (4) measurements of wall rock strata within Erebus and Victoria craters that provide compelling evidence of formation by aeolian sand deposition, with local reworking within ephemeral lakes; (5) determination that the stratigraphy exposed in the walls of Victoria and Endurance craters show an enrichment of chlorine and depletion of magnesium and sulfur with increasing depth. This result implies that regional-scale aqueous alteration took place before formation of these craters. Most recently, Opportunity has been traversing toward the ancient Endeavour crater. Orbital data show that clay minerals are exposed on its rim. Hydrated sulfate minerals are exposed in plains rocks adjacent to the rim, unlike the surfaces of plains outcrops observed thus far by Opportunity. With continued mechanical health, Opportunity will reach terrains on and around Endeavour's rim that will be markedly different from anything examined to date

Opportunity Mars Rover mission: Overview and selected results from Purgatory ripple to traverses to Endeavour crater

Opportunity has been traversing the Meridiani plains since 25 January 2004 (sol 1), acquiring numerous observations of the atmosphere, soils, and rocks. This paper provides an overview of key discoveries between sols 511 and 2300, complementing earlier papers covering results from the initial phases of the mission. Key new results include (1) atmospheric argon measurements that demonstrate the importance of atmospheric transport to and from the winter carbon dioxide polar ice caps; (2) observations showing that aeolian ripples covering the plains were generated by easterly winds during an epoch with enhanced Hadley cell circulation; (3) the discovery and characterization of cobbles and boulders that include iron and stony‐iron meteorites and Martian impact ejecta; (4) measurements of wall rock strata within Erebus and Victoria craters that provide compelling evidence of formation by aeolian sand deposition, with local reworking within ephemeral lakes; (5) determination that the stratigraphy exposed in the walls of Victoria and Endurance craters show an enrichment of chlorine and depletion of magnesium and sulfur with increasing depth. This result implies that regional‐scale aqueous alteration took place before formation of these craters. Most recently, Opportunity has been traversing toward the ancient Endeavour crater. Orbital data show that clay minerals are exposed on its rim. Hydrated sulfate minerals are exposed in plains rocks adjacent to the rim, unlike the surfaces of plains outcrops observed thus far by Opportunity. With continued mechanical health, Opportunity will reach terrains on and around Endeavour&rsquo;s rim that will be markedly different from anything examined to date.Additional co-authors: RM Haberle, KE Herkenhoff, JA Herman, KD Iagnemma, BL Jolliff, JR Johnson, G Klingelhöfer, AH Knoll, AT Knudson, R Li, SM McLennan, DW Mittlefehldt, RV Morris, TJ Parker, MS Rice, LA Soderblom, SW Squyres, RJ Sullivan, MJ Wolf

Rough-terrain mobile robot planning and control with application to planetary exploration

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.Includes bibliographical references (leaves 119-130).Future planetary exploration missions will require mobile robots to perform difficult tasks in highly challenging terrain, with limited human supervision. Current motion planning and control algorithms are not well suited to rough-terrain mobility, since they generally do not consider the physical characteristics of the rover and its environment. Failure to understand these characteristics could lead to rover entrapment and mission failure. In this thesis, methods are presented for improved rough-terrain mobile robot mobility, which exploit fundamental physical models of the rover and terrain. Wheel-terrain interaction has been shown to be critical to rough terrain mobility. A wheel-terrain interaction model is presented, and a method for on-line estimation of important model parameters is proposed. The local terrain profile also strongly influences robot mobility. A method for on-line estimation of wheel-terrain contact angles is presented. Simulation and experimental results show that wheel-terrain model parameters and contact angles can be estimated on-line with good accuracy. Two rough-terrain planning algorithms are introduced. First, a motion planning algorithm is presented that is computationally efficient and considers uncertainty in rover sensing and localization. Next, an algorithm for geometrically reconfiguring the rover kinematic structure to optimize tipover stability margin is presented. Both methods utilize models developed earlier in the thesis.(cont.) Simulation and experimental results on the Jet Propulsion Laboratory Sample Return Rover show that the algorithms allow highly stable, semi-autonomous mobility in rough terrain. Finally, a rough-terrain control algorithm is presented that exploits the actuator redundancy found in multi-wheeled mobile robots to improve ground traction and reduce power consumption. The algorithm uses models developed earlier in the thesis. Simulation and experimental results show that the algorithm leads to improved wheel thrust and thus increased mobility in rough terrain.by Karl David Iagnemma.Ph.D

Planetary Rover Inertial Navigation Applications: Pseudo Measurements and Wheel Terrain Interactions

Accurate localization is a critical component of any robotic system. During planetary missions, these systems are often limited by energy sources and slow spacecraft computers. Using proprioceptive localization (e.g., using an inertial measurement unit and wheel encoders) without external aiding is insufficient for accurate localization. This is mainly due to the integrated and unbounded errors of the inertial navigation solutions and the drifted position information from wheel encoders caused by wheel slippage. For this reason, planetary rovers often utilize exteroceptive (e.g., vision-based) sensors. On the one hand, localization with proprioceptive sensors is straightforward, computationally efficient, and continuous. On the other hand, using exteroceptive sensors for localization slows rover driving speed, reduces rover traversal rate, and these sensors are sensitive to the terrain features. Given the advantages and disadvantages of both methods, this thesis focuses on two objectives. First, improving the proprioceptive localization performance without significant changes to the rover operations. Second, enabling adaptive traversability rate based on the wheel-terrain interactions while keeping the localization reliable. To achieve the first objective, we utilized the zero-velocity, zero-angular rate updates, and non-holonomicity of a rover to improve rover localization performance even with the limited available sensor usage in a computationally efficient way. Pseudo-measurements generated from proprioceptive sensors when the rover is stationary conditions and the non-holonomic constraints while traversing can be utilized to improve the localization performance without any significant changes to the rover operations. Through this work, it is observed that a substantial improvement in localization performance, without the aid of additional exteroceptive sensor information. To achieve the second objective, the relationship between the estimation of localization uncertainty and wheel-terrain interactions through slip-ratio was investigated. This relationship was exposed with a Gaussian process with time series implementation by using the slippage estimation while the rover is moving. Then, it is predicted when to change from moving to stationary conditions by mapping the predicted slippage into localization uncertainty prediction. Instead of a periodic stopping framework, the method introduced in this work is a slip-aware localization method that enables the rover to stop more frequently in high-slip terrains whereas stops rover less frequently for low-slip terrains while keeping the proprioceptive localization reliable