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Abstract Sensing for wearable robots is an ongoing challenge, especially given the recent trend of soft and compliant robots. Recently, a wearable origami exoshell has been designed to sense the user’s torso motion and provide mobility assistance. The materials of the exoshell contribute to a lightweight design with compliant joints, which are ideal characteristics for a wearable device. Common sensors are not ideal for the exoshell as they compromise these design characteristics. Rotary encoders are often rigid metal devices that add considerable weight and compromise the flexibility of the joints. Inertial measurement unit sensors are affected by environments with variable electromagnetic fields and therefore not ideal for wearable applications. Hall effect sensors and gyroscopes are utilized as alternative compatible sensors, which introduce their own set of challenges: noisy measurements and drift due to sensor bias. To mitigate this, we designed the Kinematically Constrained Kalman filter for sensor fusion of gyroscopes and Hall effect sensors, with the goal of estimating the human’s torso and robot joint angles. We augmented the states to consider bias related to the torso angle in order to compensate for drift. The forward kinematics of the robot is incorporated into the Kalman filter as state constraints to address the unobservability of the torso angle and its related bias. The proposed algorithm improved the estimation performance of the torso angle and its bias, compared to the individual sensors and the standard Kalman filter, as demonstrated through bench tests and experiments with a human user. 

Skins with asymmetric kirigami scales and soft spikes are integrated to the surface of a base self‐burrowing robot, which consists of a soft one‐segment extending actuator. Friction anisotropy is observed at the interfaces between the burrowing robots and different granular materials. Its effects on the pulling resistance and burrowing characteristics are studied. The results demonstrate that the development of friction and friction anisotropy is affected by the characteristics of the granular material, the asymmetric skins, and the relative size of the asymmetric features to the granular particles. Robots with scales or spikes aligned along the upward direction burrow faster than those aligned against the upward direction, especially in relatively coarser granular materials. Particle image velocimetry analysis on the particle displacement fields around the actuator reveals the complexity of dry granular material interactions with soft robots, implying that aligned scales or spikes can impact the distribution of friction preferentially, opening up many possibilities for thoughtful material and geometry‐based manipulation of friction in the design and optimization of future soft burrowing robots for more versatile locomotion capabilities.