Proximity and Visuotactile Point Cloud Fusion for Contact Patches in Extreme Deformation

Equipping robots with the sense of touch is critical to emulating the capabilities of humans in real world manipulation tasks. Visuotactile sensors are a popular tactile sensing strategy due to data output compatible with computer vision algorithms and accurate, high resolution estimates of local object geometry. However, these sensors struggle to accommodate high deformations of the sensing surface during object interactions, hindering more informative contact with cm-scale objects frequently encountered in the real world. The soft interfaces of visuotactile sensors are often made of hyperelastic elastomers, which are difficult to simulate quickly and accurately when extremely deformed for tactile information. Additionally, many visuotactile sensors that rely on strict internal light conditions or pattern tracking will fail if the surface is highly deformed. In this work, we propose an algorithm that fuses proximity and visuotactile point clouds for contact patch segmentation that is entirely independent from membrane mechanics. This algorithm exploits the synchronous, high-res proximity and visuotactile modalities enabled by an extremely deformable, selectively transmissive soft membrane, which uses visible light for visuotactile sensing and infrared light for proximity depth. We present the hardware design, membrane fabrication, and evaluation of our contact patch algorithm in low (10%), medium (60%), and high (100%+) membrane strain states. We compare our algorithm against three baselines: proximity-only, tactile-only, and a membrane mechanics model. Our proposed algorithm outperforms all baselines with an average RMSE under 2.8mm of the contact patch geometry across all strain ranges. We demonstrate our contact patch algorithm in four applications: varied stiffness membranes, torque and shear-induced wrinkling, closed loop control for whole body manipulation, and pose estimation

Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion

Implementing dynamic locomotion behaviors on legged robots requires a high-quality state estimation module. Especially when the motion includes flight phases, state-of-the-art approaches fail to produce reliable estimation of the robot posture, in particular base height. In this paper, we propose a novel approach for combining visual-inertial odometry (VIO) with leg odometry in an extended Kalman filter (EKF) based state estimator. The VIO module uses a stereo camera and IMU to yield low-drift 3D position and yaw orientation and drift-free pitch and roll orientation of the robot base link in the inertial frame. However, these values have a considerable amount of latency due to image processing and optimization, while the rate of update is quite low which is not suitable for low-level control. To reduce the latency, we predict the VIO state estimate at the rate of the IMU measurements of the VIO sensor. The EKF module uses the base pose and linear velocity predicted by VIO, fuses them further with a second high-rate IMU and leg odometry measurements, and produces robot state estimates with a high frequency and small latency suitable for control. We integrate this lightweight estimation framework with a nonlinear model predictive controller and show successful implementation of a set of agile locomotion behaviors, including trotting and jumping at varying horizontal speeds, on a torque-controlled quadruped robot.Comment: Submitted to IEEE International Conference on Robotics and Automation (ICRA), 202

Value of a UK medical degree for international students (VISION): a cross-sectional study

Objectives: It is estimated that NHS staff consist of over 200 different nationalities, with a reported 30.7% of doctors holding a nationality other than British. Despite this, international medical students represent 7.5% of all medical students studying in the UK and pay on average, 4–6 times more in tuition fees when compared with the £9250 per annum (Great British Pounds (£) in 2021) paid by home students. This study’s aim and objective are to evaluate the perception of the financial cost and value of the UK medical degree for international students and their motivations for pursuing such a degree. Methods: This is a cross-sectional observational study enquiring about international premedical, medical and medical school graduates’ perception of the value of the UK medical degree and factors influencing their decision to study in the UK. A questionnaire was developed and distributed to 24 medical schools and 64 secondary schools both internationally and across the UK. Results: A total of 352 responses from 56 nationalities were recorded. 96% of international students identified clinical and academic opportunities as the most important factors to study medicine in the UK, closely followed by quality of life (88%). The least important factor was family reasons, with 39% of individuals identifying this factor. Only 4.82% of graduates in our study considered leaving the UK after training. Overall, 54% of students felt the UK degree was value for money. This belief was significantly higher in premedical students compared with existing students and graduates (71% vs 52% and 20%, p<0.001 for all comparisons). Conclusion: The quality of medical education and international prestige are attractive factors for international students to study medicine in the UK. However, further work is needed to ascertain reasons for the differing perceptions of the value by international students at different stages in their clinical training

The Politics of the Minimum Wage Debate: An Analysis of Fast Food Workers in the State of New York

The minimum wage is a charged issue across the United States. Republicans and Democrats strongly disagree on whether a minimum wage should exist and if so, what it should be. Proponents of the minimum wage see it as a way to grow the overall prosperity of a society by increasing the consumption of low wage workers, who have more money to spend with a higher wage. Others suggest that the exact opposite will happen if the minimum wage reduces employment, hurting those it was supposed to help. However, whenever the minimum wage has been instituted, it has been increased in a jurisdiction, whether it be a city, a state or a country. New York State is among the first to increase the minimum wage for a certain subset of society, franchise fast food workers, leaving others who do not work in this niche at a reduced wage. This is important for two reasons. One, this piecemeal approach to raising the minimum wage is novel and merits further analysis. Two, at the immediate outset, it creates wage inequities not only between different industries (food & beverage vs. retail & others) but also within an industry (franchise fast food vs. non-franchise fast food). Given the following, this thesis studies the political and economic ramifications of the revised minimum wage law in Upstate New York by considering the case of franchise fast food restaurants in New York State. An analysis of the different stakeholders in the process suggests that there are many different implications that the law at present does not take into account. The primary impetus for raising the minimum wage for franchise fast food workers was that their wage was not a livable wage and thus, taxpayers paid a significant amount of money in public assistance to subsidize these low wage workers. The proposition for raising the minimum wage for this part of the population was that public assistance spending would go down, thereby saving taxpayers money in the long run. My hypothesis was that while noble in its goal, the revised minimum wage laws in New York State are too narrowly defined to have a significant impact on public assistance spending. The simulations performed in Chapter IV confirm my hypothesis. An increased minimum wage for all citizens of New York State leads to far greater reductions in public assistance than when the minimum wage is only increased for franchise fast food workers. By studying the relationship between increasing the minimum wage for a subset of society relative to raising the minimum wage for the entire society and studying its relationship with public assistance spending, a starting point has been established for further research

BiConMP: a nonlinear model predictive control framework for whole body motion planning

Online planning of whole-body motions for legged robots is challenging due to the inherent nonlinearity in the robot dynamics. In this work, we propose a nonlinear model predictive control (MPC) framework, the BiConMP which can generate whole body trajectories online by efficiently exploiting the structure of the robot dynamics. BiConMP is used to generate various cyclic gaits on a real quadruped robot and its performance is evaluated on different terrain, countering unforeseen pushes, and transitioning online between different gaits. Furthermore, the ability of BiConMP to generate nontrivial acyclic whole-body dynamic motions on the robot is presented. The same approach is also used to generate various dynamic motions in MPC on a humanoid robot (Talos) and another quadruped robot (AnYmal) in simulation. Finally, an extensive empirical analysis on the effects of planning horizon and frequency on the nonlinear MPC framework is reported and discussed

Rapid convex optimization of centroidal dynamics using block coordinate descent

In this paper we explore the use of block coordinate descent (BCD) to optimize the centroidal momentum dynamics for dynamically consistent multi-contact behaviors. The centroidal dynamics have recently received a large amount of attention in order to create physically realizable motions for robots with hands and feet while being computationally more tractable than full rigid body dynamics models. Our contribution lies in exploiting the structure of the dynamics in order to simplify the original non-convex problem into two convex subproblems. We iterate between these two subproblems for a set number of iterations or until a consensus is reached. We explore the properties of the proposed optimization method for the centroidal dynamics and verify in simulation that motions generated by our approach can be tracked by the quadruped Solo12. In addition, we compare our method to a recently proposed convexification using a sequence of convex relaxations as well as a more standard interior point method used in the off-the-shelf solver IPOPT to show that our approach finds similar, if not better, trajectories (in terms of cost), and is more than four times faster than both approaches. Finally, compared to previous approaches, we note its practicality due to the convex nature of each subproblem which allows our method to be used with any off-the-shelf quadratic programming solver