Outdoor Terrain Research Articles

A Dynamic-Model-Based Wheel Slip Detector for Mobile Robots on Outdoor Terrain

This paper introduces a model-based approach to estimating longitudinal wheel slip and detecting immobilized conditions of autonomous mobile robots operating on outdoor terrain. A novel tire traction/braking model is presented and used to calculate vehicle dynamic forces in an extended Kalman filter framework. Estimates of external forces and robot velocity are derived using measurements from wheel encoders, inertial measurement unit, and GPS. Weak constraints are used to constrain the evolution of the resistive force estimate based upon physical reasoning. Experimental results show the technique accurately and rapidly detects robot immobilization conditions while providing estimates of the robot's velocity during normal driving. Immobilization detection is shown to be robust to uncertainty in tire model parameters. Accurate immobilization detection is demonstrated in the absence of GPS, indicating the algorithm is applicable for both terrestrial applications and space robotics.

Monte Carlo localization in outdoor terrains using multilevel surface maps

AbstractWe propose a novel combination of techniques for robustly estimating the position of a mobile robot in outdoor environments using range data. Our approach applies a particle filter to estimate the full six‐dimensional state of the robot and utilizes multilevel surface maps, which, in contrast to standard elevation maps, allow the robot to represent vertical structures and multiple levels in the environment. We describe probabilistic motion and sensor models to calculate the proposal distribution and to evaluate the likelihood of observations. We furthermore describe an active localization approach that actively selects the sensor orientation of the two‐dimensional laser range scanner to improve the localization results. To efficiently calculate the appropriate orientation, we apply a clustering operation on the particles and evaluate potential orientations on the basis of these clusters. Experimental results obtained with a mobile robot in large‐scale outdoor environments indicate that our approach yields robust and accurate position estimates. The experiments also demonstrate that multilevel surface maps lead to a significantly better localization performance than standard elevation maps. They additionally show that further accuracy is obtained from the active sensing approach. © 2008 Wiley Periodicals, Inc.

Frequency response method for terrain classification in autonomous ground vehicles

Many autonomous ground vehicle (AGV) missions, such as those related to agricultural applications, search and rescue, or reconnaissance and surveillance, require the vehicle to operate in difficult outdoor terrains such as sand, mud, or snow. To ensure the safety and performance of AGVs on these terrains, a terrain-dependent driving and control system can be implemented. A key first step in implementing this system is autonomous terrain classification. It has recently been shown that the magnitude of the spatial frequency response of the terrain is an effective terrain signature. Furthermore, since the spatial frequency response is mapped by an AGV's vibration transfer function to the frequency response of the vibration measurements, the magnitude of the latter frequency responses also serve as a terrain signature. Hence, this paper focuses on terrain classification using vibration measurements. Classification is performed using a probabilistic neural network, which can be implemented online at relatively high computational speeds. The algorithm is applied experimentally to both an ATRV-Jr and an eXperimental Unmanned Vehicle (XUV) at multiple speeds. The experimental results show the efficacy of the proposed approach.

BigDog, the Rough-Terrain Quadruped Robot

Less than half the Earth's landmass is accessible to existing wheeled and tracked vehicles. But people and animals using their legs can go almost anywhere. Our mission at Boston Dynamics is to develop a new breed of rough-terrain robots that capture the mobility, autonomy and speed of living creatures. Such robots will travel in outdoor terrain that is too steep, rutted, rocky, wet, muddy, and snowy for conventional vehicles. They will travel in cities and in our homes, doing chores and providing care, where steps, stairways and household clutter limit the utility of wheeled vehicles. Robots meeting these goals will have terrain sensors, sophisticated computing and power systems, advanced actuators and dynamic controls. We will give a status report on BigDog, an example of such rough-terrain robots.

Hough based terrain classification for realtime detection of drivable ground

AbstractThe usability of mobile robots for surveillance and search and rescue missions can be significantly improved by adding intelligent functionalities that decrease the cognitive load on the operator or that even allow autonomous behavior of the robots, e.g., when communication fails. Mobility in this regard is not only the mechatronic endeavor of developing suited locomotion apparatuses, but also a perception, modeling, and planning challenge. Here, the perception issue of detecting drivable ground is addressed, a particularly important issue for safety, security, and rescue robots, which have to operate in a vast range of unstructured, challenging environments. The simple yet efficient approach is based on the Hough transform of planes. The idea is to design the parameter space such that drivable surfaces can be easily detected by the number of hits in the bins corresponding to drivability. A decision tree on the bin properties increases robustness as it allows the robot to handle uncertainties, especially sensor noise. In addition to the binary distinction of drivable/nondrivable ground, a classification of terrain types is possible. The algorithm is applied to 3D data obtained from two different sensors, namely, a near‐infrared time of flight camera and a stereo camera. Experimental results are presented for typical indoor as well as outdoor terrains, demonstrating robust realtime detection of drivable ground. Seven datasets recorded indoors and outdoors under very varying conditions are used for this purpose. About 6800 snapshots of range data are processed in total. It is shown that drivability can be robustly detected with success rates ranging between 83% and 100%. Computation is extremely fast in the order of 5 to 50 ms. © 2008 Wiley Periodicals, Inc.

Mobile Traversal Schemes based on Triangulation Coverage

In harsh outdoor terrains like disaster areas and urban toxic regions, optimal placements of static sensor nodes might not be possible, leading to possible incomplete coverage of the region. In such situations, mobile sensor nodes (MSNs) might be a better option and a significantly fewer number of nodes are required than their static counterparts. A triangulation-based coverage where, groups of three MSNs position themselves to form equilateral triangles, has several applications in localization, 3D imaging and coordinated search operation. In this paper, we present several mobile traversal algorithms (MTA) based on triangulation coverage that employs N ≥ 3 MSNs such that, up to N - 3 node failures can be tolerated. MTA achieves three objectives: (a) as N increases, the total time to cover the field decreases in the absence of a failure; (b) each MSN travels a minimum distance; (c) upon a failure, the remaining MSNs efficiently complete the coverage of the field. The bounds on the total traveling distance and time are derived and the tightness of the bounds are proven through simulations. Furthermore, we also derive the bounds on the distance traveled by an MSN to complete the coverage process. The bounds on the individual traveling distances are useful in minimizing and bounding the energy consumption of the MSNs.

Criterion Validity of the StepWatch Activity Monitor as a Measure of Walking Activity in Patients After Stroke

Mudge S, Stott NS, Walt SE. Criterion validity of the StepWatch Activity Monitor as a measure of walking activity in patients after stroke. Objectives To test the validity of the StepWatch Activity Monitor (SAM) in subjects with stroke against 2 criterion standards, 3-dimensional gait analysis (3-DGA) and footswitches in a variety of indoor and outdoor walking conditions, including different speeds and different terrains, and to test the accuracy of the SAM when worn on the paretic limb. Design Criterion standard validation study. Setting Gait laboratory and outside course. Participants Twenty-five participants with physical disability after stroke. Interventions Not applicable. Main Outcome Measures The total step count measured simultaneously by SAM and either 3-DGA or footswitches for both paretic and nonparetic limbs. Results The total step count measured by the SAM and 3-DGA was highly correlated (nonparetic limb, r=.959; paretic limb, r=.896). The 95% limits of agreement (LOA) (derived from Bland-Altman analysis) between the SAM and 3-DGA were within ±10 steps for SAMs worn on either the nonparetic or paretic limb. The total step count measured simultaneously by the SAM and footswitches was also highly correlated for each limb (nonparetic, r=.999; paretic, r=.963). The 95% LOA between the SAM and footswitches were ±9 steps on the nonparetic limb but higher at ±57 steps on the paretic limb. Further analysis showed that the measurement differences occurred during the outdoor component of the combined walk. The 95% LOA between footswitches on both limbs were not more than ±9 steps for walking, suggesting that the error was accounted for by the SAM on the paretic limb, which both over- and underread the total step count in the outdoor walking conditions. Conclusions Criterion validity of the SAM to measure steps in both clinical and natural environments has been established when used on the nonparetic limb. However, more errors are apparent when the SAM is worn on the paretic limb while walking over a variety of outdoor terrains. Validation is recommended before use in patients with neurologic conditions affecting bilateral legs because there may be more error, particularly in outdoor activities.

An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing

Elevation maps are a popular data structure for representing the environment of a mobile robot operating outdoors or on not-flat surfaces. Elevation maps store in each cell of a discrete grid the height of the surface at the corresponding place in the environment. However, the use of this 2½-dimensional representation, is disadvantageous when utilized for mapping with mobile robots operating on the ground, since vertical or overhanging objects cannot be represented appropriately. Furthermore, such objects can lead to registration errors when two elevation maps have to be matched. In this paper, an approach is proposed that allows a mobile robot to deal with vertical and overhanging objects in elevation maps. The approach classifies the points in the environment according to whether they correspond to such objects or not. Also presented is a variant of the ICP algorithm that utilizes the classification of cells during the data association. Additionally, it is shown how the constraints computed by the ICP algorithm can be applied to determine globally consistent alignments. Experiments carried out with a real robot in an outdoor environment demonstrate that the proposed approach yields highly accurate elevation maps even in the case of loops. Experimental results are presented demonstrating that that the proposed classification increases the robustness of the scan matching process.

Visual wheel sinkage measurement for planetary rover mobility characterization

Wheel sinkage is an important indicator of mobile robot mobility in natural outdoor terrains. This paper presents a vision-based method to measure the sinkage of a rigid robot wheel in rigid or deformable terrain. The method is based on detecting the difference in intensity between the wheel rim and the terrain. The method uses a single grayscale camera and is computationally efficient, making it suitable for systems with limited computational resources such as planetary rovers. Experimental results under various terrain and lighting conditions demonstrate the effectiveness and robustness of the algorithm.

The VolksBot Concept – Rapid Prototyping for real-life Applications in Mobile Robotics (Das VolksBot Konzept – Ein Baukastensystem für anwendungsnahes Rapid-Prototyping mobiler Roboter)

Summary VolksBot is a modular mobile robot construction kit, developed during the last 3 years to fit the needs in research and education as well as in application-based rapid prototyping. The component-based approach offers a plug-in architecture with open interfaces in electronic hardware, software and mechanics. The lean and open structure fosters reusability of existing modules, both in hardware and software. Initially this concept was successfully applied to indoor applications. The article addresses this concept and shows how it was extended to fit the higher demands of real-life scenarios like outdoor or rough terrain. As a result, the VolksBot RT (Rough Terrain) construction kit is presented. Examples are given, how domain-specific rapid prototyping of variants of such platforms could be achieved in the fields of Urban Search and Rescue and Autonomous Transportation.

A class of intelligent agents for coordinated control of outdoor terrain mapping UGVs

This article develops a systems- and control-oriented intelligent agent framework called the hybrid intelligent control agent (HICA) and describes its composition into multiagent systems. It is essentially developed around a hybrid control system core so that knowledge-based planning and coordination can be integrated with verified hybrid control primitives to achieve the coordinated control of multiple multi-mode dynamical systems. The scheme is applied to the control of a team of unmanned ground vehicles (UGVs) engaged in an outdoor terrain mapping task. Results are demonstrated experimentally.

On Modeling Center of Foot Pressure Distortion Through a Medium

The center of foot pressure (COP) is a commonly used output measure of the postural control system as it is indicative of the systems stability. A dense piece of foam, i.e., a sponge, can be used to emulate random environmental conditions that distort the ground reaction forces received and interpreted by the cutaneous sensors in the feet; thus introducing uncertainty into the control system. In this paper, the density and size of the sponge was selected such that a subject's weight did not cause full compression. In general, the COP is measured from the bottom of the sponge. As the sponge is used to distort ground reaction forces, it is reasonable then to assume that the COP signal would also be distorted. The use of other sensory information to identify state of balance, and compute necessary balance adjustments, is therefore required. In addition to a sponge, many different types of specialized footwear and inserts are used for people with peripheral neuropathy, such as diabetics. However, it is difficult to design diabetic footwear without a better understanding of the mechanical and physiological effects that different surfaces typical of outdoor terrains, such as a sponge, which cannot be predicted without the sense of the foot, have on balance. Therefore, the goal of this study was to investigate the change of the COP signal from the top and bottom of the sponge. Portable force sensing mats from Vista Medical were used to obtain the COP from the top and bottom of the sponge. The COP measured on the bottom of the sponge is not the same as the COP measured on the top, particularly in the medial-lateral direction. Several linear and nonlinear models were used to identify the unknown plant; i.e., the sponge. Overall, the nonlinear neural network method had superior performance when compared with the linear models. Thus, the results indicate that the signals from the top and bottom of the sponge are in fact different, and furthermore, they are nonlinearly related. A nonlinear mathematical model is proposed which describes COP distortion through a medium such as a sponge. Although the values for the model parameters determined were for a particular sponge, this study suggests that a neural network plant identification model may be applied to any medium other than the sponge; the information can then be used to determine how the balance control model is affected given the sensory information received.

EXPERIMENTAL FAULT DETECTION AND ACCOMMODATION FOR AN AGRICULTURAL MOBILE ROBOT

This paper presents a systematic procedure to achieve fault tolerant capability for a four-wheel driven, four-wheel steered mobile robot moving in outdoor terrain. The procedure is exemplified through the paper by applying on a compass module. Detailed methods for fault detection and fault accommodation for the compass faults are discussed and the results are verified through field tests.

Distributed Cooperative Outdoor Multirobot Localization and Mapping

The subject of this article is a scheme for distributed outdoor localization of a team of robots and the use of the robot team for outdoor terrain mapping. Localization is accomplished via Extended...

Approximate reasoning for safety and survivability of planetary rovers

Operational safety and health monitoring are critical matters for autonomous planetary rovers operating on remote and challenging terrain. This paper describes rover safety issues and presents an approximate reasoning approach to maintaining vehicle safety in a navigational context. The proposed rover safety module is composed of two distinct behaviors: safe attitude (pitch and roll) management and safe traction management. Fuzzy logic implementations of these behaviors on outdoor terrain are presented. Sensing of vehicle safety coupled with visual neural network-based perception of terrain quality are used to infer safe speeds during rover traversal. In addition, approximate reasoning for self-regulation of internal operating conditions is briefly discussed. The core theoretical foundations of the applied soft computing techniques are presented and supported by descriptions of field tests and laboratory experimental results. For autonomous rovers, the approach provides intrinsic safety cognizance and a capacity for reactive mitigation of navigation risks.

Geometric reasoning under uncertainty for map-basedlocalization

Map-based navigation in outdoor terrain lacking man-made structures or other highly distinctive landmarks can produce severe localization problems. This paper presents an approach to navigation which implements high level geometric reasoning and matching strategies based on those used by skilled human navigators. This approach, which is demonstrated on a real example involving imagery of mountainous terrain obtained with a video camera and USGS map data, is designed to avoid many of the pitfalls occurring when an attempt is made to navigate by modeling the environment mathematically. It exploits feature attributes which cannot be easily expressed quantitatively but are central to the successful human navigation process.

The rhetoric of space: Literary and artistic representations of landscape in Republican and Augustan Rome

Horace's famous Ut pictura poesis serves as the point of departure for this book. It is a much discussed passage, in our time and in the past, because it has been subjected to widely divergent interpretations. This follows from the assumption that Horace meant pictures are like poems. Leach, however, argues he meant no such thing; instead, he compared the ways visual and literary works address themselves to the beholder, an aesthetics and semiology of reception, not expression. The subject matter of this book is ancient Roman landscape, not gardens per se, nor cities, although architectural settings (and sets) are discussed; rather, Leach explores the sort of outdoor terrain, in pictures and poems that serves as the site of events: for example, harbours, hillsides, battlefields and temple compounds as places of arrival and departure, epiphany, war and religious rite. The sources examined range from the writings of Virgil, Caesar, Lucretius, Varro, Horace, Pliny, Propertius and Ovid to the panel and fresco paintings in Rome, Naples, Pompeii and elsewhere. The wide and inclusive expanse of Leach's �landscape� makes the book very long, seemingly wandering in places and nearly intractable as a whole. The argument is best sustained at a local level when specific writings and works are considered, especially those of Virgil in the context of the Odyssey landscapes.

R & D Profile Jet Propulsion Laboratory Robotic Facilities and Associated Research

SUMMARYThis paper describes the robotics facilities and associated research program of the Jet Propulsion Laboratory, lead center in telerobotics for the United States National Aeronautics and Space Administration. Emphasis is placed on evolution from teleoperation to remote System automation. Research is described in manipulator modelling and control, real-time planning and monitoring, navigation in outdoor terrain, real-time sensing and perception, human-machine interface, and overall System architectures. Applications to NASA missions emphasize robotic spacecraft for solar System exploration, satellite servicing and retrieval, assembly of structures, and surveillance. Applications to military missions include battlefield navigation, surveillance, logistics, command and control.