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Mobile robots are increasingly being used in high-risk rough terrain situations, such as planetary exploration and military applications. Current control and localization algorithms are not well suited to rough terrain, since they generally do not consider the physical characteristics of the vehicle and its environment. Little attention has been devoted to the study of the dynamic effects occurring at the wheel-terrain interface, such as slip and sinkage. These effects compromise odometry accuracy, traction performance, and may even result in entrapment and consequent mission failure. This paper describes methods for wheel slippage and sinkage detection aiming at improving vehicle mobility on soft sandy terrain. Novel measures for wheel slip detection are presented based on observing different onboard sensor modalities and defining deterministic conditions that indicate vehicle slippage. An innovative vision-based algorithm for wheel sinkage estimation is discussed based on edge detection strategy. Experimental results, obtained with a Mars rover-type robot operating in high-slippage sandy environments and with a wheel sinkage testbed, are presented to validate our approach. It is shown that these techniques are effective in detecting wheel slip and sinkage.