Introduction: Vehicle–Terrain Interactionfor Mobile Robots

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The application of mobile robots to field environments hasenabled significant advances in such diverse areas as agri-culture, defense and security, planetary surface exploration,and mining. To successfully deploy a robot in an unstruc-tured, outdoor environment, roboticists should considerthe interaction of the robot and terrain. Often, this inter-action is assumed to follow a simple Coulomb friction law,and the effects of such phenomena as wheel (or track, orfoot) slippage and sinkage are ignored.

Although such an approach may be sufficient forsome applications, operation near a system’s performancelimits—that is, at high speeds, or in challenging terrain—often requires more sophisticated analyses of robot–terraininteraction. This has implications for the system’s design,sensing subsystem, and estimation and control algorithms.The properties of terrain that can significantly influencerobot performance include the following:

• Geometry, particularly terrain slope and roughness.Movement over sloped terrain is subject to destabilizingevents such as rollover and skidding. Terrain roughnesscan perturb a robot’s pose and thus disrupt sensor point-ing and stabilization. Disturbances arising from bothslope and roughness can also lead to errors in path track-ing and localization. Finally, severe slope and roughnesscan completely impair vehicle motion.

• Appearance properties, particularly color, texture, andreflectivity. These properties are often exploited forpurposes of environmental classification and visualodometry calculations, and the uniformity of appear-ance properties in a scene often dictates the degree ofdifficulty of algorithmic implementation. Scenes withhighly uniform appearance properties can pose a chal-lenge to classical feature extraction techniques.

• Mechanical properties, namely shear strength and stiff-ness. Travel over terrain that exhibits low shear strengthand stiffness can be difficult due to resulting runninggear slip and sinkage. Significant slip and sinkage canresult in reduced thrust and increased motion resistance,which can cause path tracking and localization errors.Such terrain might even comprise an impassible obsta-cle, despite its benign geometry.

This special issue of the Journal of Field Robotics focuses onrecent advances in research areas related to robot–terraininteraction. Six technical papers are presented that addresssome of the above-mentioned issues through a study of me-chanical design, sensing algorithm development, and/orcontrol algorithm development.

In the article by Fauroux and Vaslin, the distribution ofwheel–terrain contact force is controlled to achieve powerreduction and performance improvement for a skid-steeredvehicle. The study is based on an all-terrain 6×6 electricwheelchair, the Kokoon mobile platform. Skid steering ismodeled with emphasis on relating terrain contact forceswith the vehicle’s mass distribution. Experimental resultsare presented that show that skid steering can be improvedby adjustments to the suspension kinematic properties.Such adjustments are shown to decrease the required longi-tudinal forces applied by the engine and improve the steer-ing ability of the vehicle.

The paper by Low and Wang addresses the problemof path following for wheeled robots in the presence ofskidding and slipping. Well-known vehicle models are aug-mented to explicitly consider skidding and slipping, andcontrol laws are proposed using the integrator backstep-ping technique. Simulation and experimental results showthat the proposed control methods can effectively compen-sate for wheel skidding and slipping in field environmentsto enable a vehicle to accurately follow a desired path.

The problem of monocular visual pose estimation inarctic environments is addressed in the paper by Williamsand Howard. In arctic environments, feature extraction ischallenging due to the uniform appearance of the sur-roundings. The authors propose a pose estimation methodthat relies on visual odometry techniques and an imagegradient boosting algorithm. Experimental results fromfield testing in Alaska demonstrate the method’s favorableperformance.

In the paper by Krebs, Predalier, and Siegwart, a frame-work is presented for learning the mechanical properties ofterrain from experience. Terrain is characterized from bothremote sensors (e.g., a camera) and local sensors (e.g., anIMU), and class estimates are formed (and probability dis-tribution functions estimated) in both “remote” and “local”

Journal of Field Robotics 27(2), 105–106 (2010) C© 2009 Wiley Periodicals, Inc.Published online in Wiley InterScience (www.interscience.wiley.com). • DOI: 10.1002/rob.20331

106 • Journal of Field Robotics—2010

subspaces. Methods for correlating remote and local sub-spaces are then described. The result is a “near-to-far” ap-proach to remote prediction of terrain physical properties.The method is demonstrated on the CRAB robot operatingin outdoor environments.

The paper by Lenain et al. addresses sideslip angle esti-mation for precise real-time vehicle control. A mixed back-stepping kinematic and dynamic observer is designed toimprove the required estimates. The idea is to use a kine-matic representation to estimate the slowly varying data,which can be used as input to a dynamic observer to sup-ply reactive sideslip angle estimation. Simulation studiesat high speed and experimental studies at lower speed areperformed to show the benefits of the proposed algorithm.

The paper by Freitas et al. presents a multiobjectivemethod for suspension reconfigurability control to im-prove robot mobility in outdoor environments. The au-thors present control strategies to improve mobility based

on ground clearance, stability, and wheel traction. A mul-tiobjective optimization process is set up to find a Paretooptimal solution. The proposed control is demonstratedthrough numerical simulations and experiments on the En-vironmental Hybrid Robot operating in the Amazon rainforest.

We hope that the papers collected here will be of inter-est to all readers of the JFR. We would like to thank SanjivSingh and Sanae Minick for their editorial and administra-tive assistance during the editing process. We would like toexpress our gratitude to the many individuals who servedas reviewers of these papers, often through several itera-tions, and contributed to their high quality.

Karl IagnemmaPhilippe Martinet

Danwei WangGuest Editors

Journal of Field Robotics DOI 10.1002/rob