Community-based locomotor training post-stroke has shown improvements in independent ambulation by increasing dose, intensity, and specificity of walking practice. Robotic ankle exoskeletons hold the potential to facilitate continued rehabilitation at home, but understanding what aspects of the design are most relevant for successful translation to the community presents a challenge. Here, we design a portable rigid ankle exoskeleton to use as a research platform for investigating the effect of assistance on post-stroke gait during overground, community-based walking. We first test our device with stroke survivors and validate its potential for future community use. We then present a systematic method for quantifying power transmission losses at each transmission stage from the battery to the wearer, using data gathered from walking trials with healthy participants. Our evaluation method revealed inefficiencies in power transfer at the interface level, likely resulting from the compliance in the structural components of the system, which motivates future redesign considerations. Overall, our method provides a framework to identify and characterize the components that must be redesigned to lower exoskeleton weight and maximize performance.

This paper presents Stanford Doggo, a quasi-direct-drive quadruped capable of dynamic locomotion. This robot matches or exceeds common performance metrics of state-of-the-art legged robots. In terms of vertical jumping agility, a measure of average vertical speed, Stanford Doggo matches the best performing animal and surpasses the previous best robot by 22%. An overall design architecture is presented with focus on our quasi-direct-drive design methodology. The hardware and software to replicate this robot is open-source, requires only hand tools for manufacturing and assembly, and costs less than $3000.

Robots performing manipulation tasks must operate under uncertainty about both their pose and the dynamics of the system. In order to remain robust to modeling error and shifts in payload dynamics, agents must simultaneously perform estimation and control tasks. However, the optimal estimation actions are often not the optimal actions for accomplishing the control tasks, and thus agents trade between exploration and exploitation. This work frames the problem as a Bayes-adaptive Markov decision process and solves it online using Monte Carlo tree search and an extended Kalman filter to handle Gaussian process noise and parameter uncertainty in a continuous space. MCTS selects control actions to reduce model uncertainty and reach the goal state nearly optimally. Certainty equivalent model predictive control is used as a benchmark to compare performance in simulations with varying process noise and parameter uncertainty.

Surgeries involving interaction with soft tissue like the brain need to minimize shear and normal forces that can cause tissue damage or hemorrhage. Other surgeries require the ability to follow a complex, curved path, such as through an intestine or to a kidney stone. This paper presents a soft catheter that has the potential to aid in these challenging cases. The soft catheter is capable of apical extension in which the tip extends while the rest of the catheter remains stationary. This limits shear forces with the environment, easing movement of a body's tip through a constrained space. The soft catheter is pre-formed to patient-specific trajectories, meaning that normal forces against tissue would only arise due to errors between the actual and desired paths; we show decrease in normal force applied to the environment on the order of 100 compared to a standard catheter in a 30 degree bend. Setting the internal pressure allows for control of catheter stiffness, with a 500 times difference over the range of tested pressures. Manual operation to reach a surgical site requires only holding the correct orientation at the entry point into the body and setting the internal pressure of the catheter. This soft catheter could offer two benefits: the ability to apply low tissue interaction forces and reach challenging locations within the body.

This paper presents the Tact hand-an anthropomorphic, open-source, myoelectric prosthetic hand that was designed for use by people with transradial amputations in developing countries. This hand matches or exceeds the performance of other state-of-the-art myoelectric prosthetic hands, but costs two orders of magnitude less ($250) and is easy to manufacture with a 3D printer and off-the-shelf parts. We describe our design process, evaluate the Tact hand with both qualitative and quantitative measures of performance, and show examples of using this hand to grasp household objects.