RESEARCH

Lookahead Navigation for High-Speed Mobile Robots
Students: Sterling Anderson and Steven Peters

Recent developments in both defense and commercial sectors have inspired a growing interest in mobile robot navigation technologies. As look-ahead sensing capabilities improve, mobile robots will be able to operate at higher speeds and in more varied environments. This research aims to develop novel planning and control approaches to meet the challenge.

Lookahead navigation project page

Omnidirectional Mobile Robots in Rough Terrain
Students: Genya Ishigami and Martin Udengaard

Mobile robots are finding increasing use in military, disaster recovery, and exploration applications. These applications frequently require operation in rough, unstructured terrain. This project focuses on the analysis, design, and control of omnidirectional mobile robots for use in rough terrain. The robots in this study use active split offset caster drive mechanisms that allow high thrust efficiency during omnidirectional motion and low ground pressures over rough terrain. The design guidelines developed in this research are scalable and applicable for a class of omnidirectional mobile robots.

Omni-directional rough terrain project page

SQUISHBot
Students: Nadia Cheng

SQUISHBot (Soft QUIet Shape-shifting robot) is a soft meso-scale robot that can climb walls, ceilings, and cross rough terrain. The robot is compliant and can morph, allowing it to conform to irregular shapes and squeeze through holes much smaller than its nominal cross-sectional area.

SQUISHBot project page

Terrain Sensing for Mobile Robots
Students: Chris Brooks

For mobile robots in rough terrain, the ability to safely traverse terrain is highly dependent on mechanical properties of that terrain. For example, a robot may be able to climb up a rocky slope with ease, but slide down a sandy slope the same grade. With mobile robots being employed for planetary exploration and UGVs being developed for missions on Earth, the ability to predict these mechanical terrain properties from a distance is becoming increasingly important.

Terrain Sensing Project Page

Mobility Prediction with Environmental Uncertainty
Students: Genya Ishigami and Gaurav Kewlani

The ability of autonomous unmanned ground vehicles to rapidly and effectively predict terrain negotiability is a critical requirement for their use on challenging terrain. Most of the work done on mobility prediction for such vehicles, however, assumes precise knowledge about the vehicle/terrain properties. In practical conditions though, uncertainties are associated with the estimation of these parameters. This work focuses on developing efficient methods that take into account environmental uncertainty while determining vehicular mobility.

Mobility Prediction Project Page