Terrain Characterization via Machine vs. Deep Learning Using Remote Sensing.

Terrain traversability is critical for developing Go/No-Go maps for ground vehicles, which significantly impact a mission's success. To predict the mobility of terrain, one must understand the soil characteristics. In-situ measurements performed in the field are the current method of collecting this information, which is time-consuming, costly, and can be lethal for military operations.

Modeling Human Steering Behavior in Haptic Shared Control of Autonomy-Enabled Unmanned Ground Vehicles.

Objective: A human steering model for teleoperated driving is extended to capture the human steering behavior in haptic shared control of autonomy-enabled Unmanned Ground Vehicles (UGVs).

Background: Prior studies presented human steering models for teleoperation of a passenger-sized Unmanned Ground Vehicle, where a human is fully in charge of driving. However, these models are not applicable when a human needs to interact with autonomy in haptic shared control of autonomy-enabled UGVs.

A workload adaptive haptic shared control scheme for semi-autonomous driving.

Haptic shared control is used to manage the control authority allocation between a human and an autonomous agent in semi-autonomous driving. Existing haptic shared control schemes, however, do not take full consideration of the human agent. To fill this research gap, this study presents a haptic shared control scheme that adapts to a human operator's workload, eyes on road and input torque in real time.

Modeling Human Steering Behavior in Teleoperation of Unmanned Ground Vehicles With Varying Speed.

Objective: This paper extends a prior human operator model to capture human steering performance in the teleoperation of unmanned ground vehicles (UGVs) in path-following scenarios with varying speed.

Background: A prior study presented a human operator model to predict human steering performance in the teleoperation of a passenger-sized UGV at constant speeds. To enable applications to varying speed scenarios, the model needs to be extended to incorporate speed control and be able to predict human performance under the effect of accelerations/decelerations and various time delays induced by the teleoperation setting.

Modeling Human Steering Behavior During Path Following in Teleoperation of Unmanned Ground Vehicles.

Objective: This paper presents a behavioral model representing the human steering performance in teleoperated unmanned ground vehicles (UGVs).

Background: Human steering performance in teleoperation is considerably different from the performance in regular onboard driving situations due to significant communication delays in teleoperation systems and limited information human teleoperators receive from the vehicle sensory system. Mathematical models capturing the teleoperation performance are a key to making the development and evaluation of teleoperated UGV technologies fully simulation based and thus more rapid and cost-effective.

Theoretical and experimental indicators of falls during pregnancy as assessed by postural perturbations.

Throughout pregnancy, women experience physical, physiological, and hormonal alterations that are often accompanied by decreased postural control. According to one study, nearly 27% of pregnant women fell while pregnant. This study had two objectives: (1) to characterize the postural responses of pregnant fallers, nonfallers, and controls to surface perturbations, and (2) to develop a mathematical model to gain insights into the postural control strategies of each group.

A mathematical model for incorporating biofeedback into human postural control.

Background: Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1) to develop a scalable method for incorporating biofeedback into postural control that is independent of the model's degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2) to validate this new model using multidirectional perturbation experimental results.