Stiffness sensing and palpation are essential for understanding object properties, including tissue health and fruit ripeness. Currently, there is limited research on using soft-tipped sensors for stiffness sensing and dynamic palpation. To address these challenges, we investigate how the pressure modulated optical tracking (PMOT) sensor can use compliance control to quantify tissue stiffness and detect margins in samples through dynamic palpation. Results show that the PMOT sensor modulus of elasticity sensing range is from 4.20 kPa up to 177.62 kPa. Across all untrained samples, elasticity was measured with a root-mean-square error (RMSE) of 7.72%. Further, it is shown that the sensor can locate margins between 13.4 kPa and embedded 29.3 kPa materials during palpation. When mounted on a linear rail, averaged for the direction of travel, the sensor's signal-to-noise ratio (SNR) was up to 39.5:1. Participants used the sensor to locate embedded margins in a teleoperation environment with visual feedback. This was achieved with an accuracy of 96.5%.

Robust mechanisms for slip resistance are an open challenge in legged locomotion. Animals such as goats show impressive ability to resist slippage on cliffs. It is not fully known what attributes in their body determine this ability. Studying the slip resistance dynamics of the goat may offer insight toward the biologically inspired design of robotic hooves. This article tests how the embodiment of the hoof contributes to solving the problem of slip resistance. We ran numerical simulations and experiments using a passive robotic goat hoof for different compliance levels of its three joints. We established that compliant yaw and pitch and stiff roll can increase the energy required to slide the hoof by ≈ 20% compared to the baseline (stiff hoof). Compliant roll and pitch allow the robotic hoof to adapt to the irregularities of the terrain. This produces an antilock braking system-like behavior of the robotic hoof for slip resistance. Therefore, the pastern and coffin joints have a substantial effect on the slip resistance of the robotic hoof, while the fetlock joint has the lowest contribution. These shed insights into how robotic hooves can be used to autonomously improve slip resistance.

The remarkable ability of goats to maintain stability during climbing cliffs or trees provides a valuable opportunity to understand some of the secrets of stable legged locomotion on unstructured terrains. This paper, for the first time, presents analytical and experimental explanations as to how the morphological computation at the goat hoof makes a significant contribution to slip reduction on both smooth and rough surfaces. We conducted experiments using a laboratory made hoof and compared its dynamic behavior against a rounded foot. We recorded forces and position of the hoof to analyze the effect of its shape and the individual contributions from 3-joints in the hoof on the work required to slip. Results state that the work required to move the hoof is more than 3 times that required to move a rounded foot. Additionally, the variables in the transient state are affected not only by the number and type of joints but also by the interaction with the environment. These findings promote the development of new types of feet for robots for all terrain conditions with greater stability and less control complexity.