Jo-Yung Wong

Bio: Jo-Yung Wong is an academic researcher from Newcastle University. The author has contributed to research in topics: Electronic differential & Axle. The author has an hindex of 1, co-authored 1 publications receiving 307 citations.

Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers

Abstract: Future planetary exploration missions will require wheeled mobile robots ("rovers") to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper, an online estimation method that identifies key terrain parameters using on-board robot sensors is presented. These parameters can be used for traversability prediction or in a traction control algorithm to improve robot mobility and to plan safe action plans for autonomous systems. Terrain parameters are also valuable indicators of planetary surface soil composition. The algorithm relies on a simplified form of classical terramechanics equations and uses a linear-least squares method to compute terrain parameters in real time. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.

Terramechanics-based model for steering maneuver of planetary exploration rovers on loose soil

Abstract: This paper presents analytical models to investigate the steering maneuvers of planetary exploration rovers on loose soil. The models are based on wheel-soil interaction mechanics, or terramechanics, with which the traction and disturbance forces of a wheel are evaluated for various slip conditions. These traction forces are decomposed into the longitudinal and lateral directions of the wheel. The latter component, termed the side force has a major influence in characterizing the steering maneuvers of the rover. In this paper, the wheel-soil mechanics models are developed with particular attention to the side force and the validity of the model is confirmed by using a single-wheel test bed. The motion profile of the entire rover is numerically evaluated by incorporating the wheel-soil models into an articulated multibody model that describes the motion dynamics of the vehicle’s body and chassis. Steering maneuvers are investigated under different steering angles by using a four-wheel rover test bed on simulated lunar soil regolith simulant. The experimental results are compared with the simulation results using the corresponding model parameters. The proposed wheel-and-vehicle model demonstrates better accuracy in predicting steering maneuvers as compared to the conventional kinematics-based model. ©

Terrain Characterization and Classification with a Mobile Robot

Abstract: This paper introduces novel methods for terrain classification and characterization with a mobile robot. In the context of this paper, terrain classification aims at associating terrains with one of a few predefined, commonly known categories, such as gravel, sand, or asphalt. Terrain characterization, on the other hand, aims at determining key parameters of the terrain that affect its ability to support vehicular traffic. Such properties are collectively called “trafficability.” The proposed terrain classification and characterization system comprises a skid-steer mobile robot, as well as some common and some uncommon but optional onboard sensors. Using these components, our system can characterize and classify terrain in real time and during the robot's actual mission. The paper presents experimental results for both the terrain classification and characterization methods. The methods proposed in this paper can likely also be implemented on tracked robots, although we did not test this option in our work.