Negotiating Uneven Terrain by a Simple Teleoperated Tracked Vehicle with Internally Movable Center of Gravity

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs at appropriate trajectories, stepping over a high obstacle. To realize a COG movable mechanism with a small number of joints, a number of UGVs have been developed that can shift their COG by moving a mass at a high position above the body. However, these tend to pose a risk of overturning, and the mass must be moved quite far to climb a high step. To address these issues, we design a novel COG shift mechanism, in which the COG can be shifted forward and backward inside the body by moving most of its internal devices. Since this movable mass includes DC motors for driving both tracks, we can extend the range of the COG movement. We demonstrate that a conventional tracked vehicle prototype can traverse a step and a gap between two steps, as well as climb stairs and a steep slope, with a human operating the vehicle movement and the movable mass position.

Assessment of CT to CBCT contour mapping for radiomic feature analysis in prostate cancer

This study provides a quantitative assessment of the accuracy of a commercially available deformable image registration (DIR) algorithm to automatically generate prostate contours and additionally investigates the robustness of radiomic features to differing contours. Twenty-eight prostate cancer patients enrolled on an institutional review board (IRB) approved protocol were selected. Planning CTs (pCTs) were deformably registered to daily cone-beam CTs (CBCTs) to generate prostate contours (auto contours). The prostate contours were also manually drawn by a physician. Quantitative assessment of deformed versus manually drawn prostate contours on daily CBCT images was performed using Dice similarity coefficient (DSC), mean distance-to-agreement (MDA), difference in center-of-mass position (ΔCM) and difference in volume (ΔVol). Radiomic features from 6 classes were extracted from each contour. Lin’s concordance correlation coefficient (CCC) and mean absolute percent difference in radiomic feature-derived data (mean |%Δ|RF) between auto and manual contours were calculated. The mean (± SD) DSC, MDA, ΔCM and ΔVol between the auto and manual prostate contours were 0.90 ± 0.04, 1.81 ± 0.47 mm, 2.17 ± 1.26 mm and 5.1 ± 4.1% respectively. Of the 1,010 fractions under consideration, 94.8% of DIRs were within TG-132 recommended tolerance. 30 radiomic features had a CCC > 0.90 and 21 had a mean |%∆|RF < 5%. Auto-propagation of prostate contours resulted in nearly 95% of DIRs within tolerance recommendations of TG-132, leading to the majority of features being regarded as acceptably robust. The use of auto contours for radiomic feature analysis is promising but must be done with caution.

The physics of people’s opinions

This paper explores the abstraction of classical physics and applies several metrics that explore the evolution of social opinion. These metrics include an abstraction of Newtonian kinematics: mass, position, speed, acceleration, and Newtonian dynamics, an abstraction of force. Poll data is fit to a 2nd-order polynomial and a logistic function. These fits are used to understand the acceleration of opinion shift, and we explore recent social, cultural, and environmental trends, such as views on global climate change. We compare our results with the evolution of communication technologies and time spent on devices over the past 120 years. We show that the model connects the evolution in opinion with an abstraction of a Galilean concept: acceleration is independent of mass. Finally, we discuss the model of social polarization and the non-linear effect of media such as echo chambers.

Optimization-based subject-specific planar human vertical jumping prediction: Effect of elbow flexion and weighted vest

Jumping strategies differ considerably depending on athletes’ physical activity demands. In general, the jumping motion is desired to have excellent performance and low injury risk. Both of these outcomes can be achieved by modifying athletes’ jumping and landing mechanics. This paper presents a consecutive study on the optimization-based subject-specific planar human vertical jumping to test different loading conditions (weighted vest) during jumping with or without elbow flexion during the arm-swing based on the validated prediction model in the first part of this study. The sagittal plane skeletal model simulates the weighting, unweighting, breaking, propulsion phases and considers four loading conditions: 0%, 5%, 10%, and 15% body weight. Results show that the maximum ground reaction forces, the body center of mass position, and velocities at the take-off instant are different for different loading conditions and with/without elbow flexion. The optimization formulation is solved using MATLAB® with 35 design variables with 197 nonlinear constraints for a five-segment body model and 42 design variables with 227 nonlinear constraints for a six-segment body model. Both models are computationally efficient, and they can predict ground reaction forces, the body center of mass position, and velocity. This work is novel in the sense that presents a simulation model capable of considering different external loading conditions and the effect of elbow flexion during arm swing.

Effects of the Weight and Balance of Head-Mounted Displays on Physical Load

To maximize user experience in VR environments, optimizing the comfortability of head-mounted displays (HMDs) is essential. To date, few studies have investigated the fatigue induced by wearing commercially available HMDs. Here, we focus on the effects of HMD weight and balance on the physical load experienced by the user. We conducted an experiment in which participants completed a shooting game while wearing differently weighted and balanced HMDs. Afterwards, the participants completed questionnaires to assess levels of discomfort and fatigue. The results clarify that the weight of the HMD affects user fatigue, with the degree of fatigue varying depending on the center of mass position. Additionally, they suggest that the torque at the neck joint corresponds to the physical load imparted by the HMD. Therefore, our results provide valuable insights, demonstrating that, to improve HMD comfortability, it is necessary to consider both the balance and reduction of weight during HMD design.

Adaptive model predictive stabilization of an electric cargo bike using a cargo load moment of inertia estimator

This paper addresses the problem of stabilizing an electric cargo bike. For most control objectives, it suffices to consider a cargo bike as a two-wheeler. However, in addition to the challenges posed to the control of traditional two-wheelers, electric cargo bikes also have the issue of the cargo load, which can significantly influence the driving behaviour. Hence, detection and estimation of the mass, position and inertial properties of the cargo load become important. Here, a Kalman filter based algorithm which estimates these parameters online is presented. For the estimation, measurements of the force exerted by the load are recorded using force sensors installed under the load. Along with these, roll angle and roll acceleration are also measured. The estimated values are then used by an adaptive model predictive controller (MPC) to adjust the model-parameters and stabilize a cargo bike while following a set trajectory.

Similar sensorimotor transformations control balance during standing and walking

Standing and walking balance control in humans relies on the transformation of sensory information to motor commands that drive muscles. Here, we evaluated whether sensorimotor transformations underlying walking balance control can be described by task-level center of mass kinematics feedback similar to standing balance control. We found that delayed linear feedback of center of mass position and velocity, but not delayed linear feedback from ankle angles and angular velocities, can explain reactive ankle muscle activity and joint moments in response to perturbations of walking across protocols (discrete and continuous platform translations and discrete pelvis pushes). Feedback gains were modulated during the gait cycle and decreased with walking speed. Our results thus suggest that similar task-level variables, i.e. center of mass position and velocity, are controlled across standing and walking but that feedback gains are modulated during gait to accommodate changes in body configuration during the gait cycle and in stability with walking speed. These findings have important implications for modelling the neuromechanics of human balance control and for biomimetic control of wearable robotic devices. The feedback mechanisms we identified can be used to extend the current neuromechanical models that lack balance control mechanisms for the ankle joint. When using these models in the control of wearable robotic devices, we believe that this will facilitate shared control of balance between the user and the robotic device.