Active safety systems enabled by steer-by-wire technology can share control with a driver, augmenting the driver's steering commands to avoid collisions and prevent loss of control. The extent to which this can be...
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ISBN:
(纸本)9781479932740
Active safety systems enabled by steer-by-wire technology can share control with a driver, augmenting the driver's steering commands to avoid collisions and prevent loss of control. The extent to which this can be done is limited by the controller's ability to anticipate dangerous scenarios in order to appropriately intervene and steer the vehicle to safety. However, the non-linear nature of tire dynamics poses a challenge in predicting and modifying vehicle behavior in real-time. In this paper, online successive linearizations of the future planned vehicle trajectory approximates these non-linear dynamics in a real-time, model predictive controller that shares control with a human driver. Simulation results of aggressive maneuvers demonstrate the usefulness of this approach as well as illustrate interesting interactions between the sometimes competing objectives of vehicle stability and collision avoidance.
Older adults often lack the ability or strength to walk or to self-propel in manual wheelchairs. However, the need for a significant level of cognitive capacity to safely operate current powered wheelchair technology ...
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ISBN:
(纸本)9781479932740
Older adults often lack the ability or strength to walk or to self-propel in manual wheelchairs. However, the need for a significant level of cognitive capacity to safely operate current powered wheelchair technology tends to exclude users with cognitive impairments. The resulting lack of mobility for a significant proportion of elderly residents in long term care leads to negative social, mental and physical outcomes. In this paper, we review shared (or collaborative) control policies implemented by smart wheelchair prototypes that have been tested by participants from their target populations, and highlight key usability findings and clinical insights. We discuss desirable features for control policies in new intelligent wheelchairs for cognitively impaired older adults. We then propose a method to evaluate these policies in a Wizard of Oz study conducted with cognitively impaired participants living in long term care facilities.
This paper presents a driver assisting system for coorperative cruising of multiple cars. In order to account for personal difference of individual drivers, each driver's vehicle following skill on expressways is ...
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ISBN:
(纸本)9781479932740
This paper presents a driver assisting system for coorperative cruising of multiple cars. In order to account for personal difference of individual drivers, each driver's vehicle following skill on expressways is identified as a PrARX model, a continuous approximation of hybrid dynamical system. The PrARX model describes the driver's logical decision making as well as continuous maneuvering in a uniform manner. The assisting acceleration is computed in the framework of model predictive control, where the plant model is a platoon of cars coupled with PrARX driver models. For computing assisting outputs in real time, a fast computation method for nonlinear model predictive control based on the continuation technique is employed. The proposed assisting system is tested in numerical simulations and on a driving simulator with a real human driver. The high speed calculation of the Homotopy method is also proved by comparison to the conventional method. Finally, the advantage of global optimization for cooperative safety is confirmed by comparing its control performance with the local optimization for individual safety.
People re-learning skills after a stroke go through the same process as someone learning to play tennis, but they have a problem because they can hardly move at all so they cannot practise, which means they dont get f...
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ISBN:
(纸本)9781479932740
People re-learning skills after a stroke go through the same process as someone learning to play tennis, but they have a problem because they can hardly move at all so they cannot practise, which means they dont get feedback. Muscles can be made to work by electrical stimulation where electrical impulses travel along the nerves in much the same way as the electrical impulses from the brain. If stimulation is carefully controlled, a useful movement can be made. This works better if the person is attempting the movement themselves;we therefore need to combine a persons own effort with just enough extra electrical stimulation to achieve the movement. Previous research with supporting clinical trial data has shown that iterative learning control can be used to regulate the electrical stimulation applied with the essential requirement that if the patient is improving with each attempt the level of voluntary effort increase and the applied stimulation decreases. This paper reports results, including patient experimental data, where wrist and hand extensors are also stimulated using a 40 element surface electrode array and thereby moves closer to facilitating the re-learning of goal oriented tasks that are essential to move this technology towards home use.
humans remain in the loop in teleoperation because they have some knowledge that the robot they are controlling does not. At the same time teleoperated robots can be programmed to be very good at many tasks, such as a...
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ISBN:
(纸本)9781479932740
humans remain in the loop in teleoperation because they have some knowledge that the robot they are controlling does not. At the same time teleoperated robots can be programmed to be very good at many tasks, such as avoiding obstacles. Therefore, sharing control between a human and semi-autonomous behaviors on a robot has great potential. This paper presents a model predictive control (MPC) shared control framework for blending human inputs with autonomous behavior inputs. This work adds consideration of how the human input differs from that of an autonomous controller in addition to threat of collision. The framework is applied to a high speed differential drive robot moving through an obstacle field. Preliminary tests by the authors compared the MPC shared control framework to switching obstacle avoidance on/off and the proposed MPC shared control gives the human up to 26% more control with a 35% reduction in collision penalty. Compared to pure humancontrol, MPC shared control demonstrated a 66% reduction in collision penalty. Results show promise for increased user control with better performance.
This paper proposes an optimal control approach to power management and pacing in an electric bicycle ride with the objective of minimizing travel time. We assume prior knowledge of upcoming terrain. Furthermore human...
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ISBN:
(纸本)9781479932740
This paper proposes an optimal control approach to power management and pacing in an electric bicycle ride with the objective of minimizing travel time. We assume prior knowledge of upcoming terrain. Furthermore human pedaling force constraints are estimated by using a phenomenological fatigue dynamics model. Using upcoming terrain information, estimated rider's state of fatigue (SOF), measured velocity, cadence, and state of charge (SOC) of the battery, the optimal solution to the problem is obtained via a three-state dynamic programming (DP) approach. The proposed solution guides the rider by suggesting an optimal reference velocity and also optimally adjusts the electric-human power split. The optimal solution is compared to aggressive and conservative rule-based strategies that we have devised. Simulation results show that travel time can be significantly reduced with the optimal control approach.
Grasping and twisting are basic motor skills for the execution of activities in daily life such as opening a door with a door knob. We study the relationship between grip force and hand trajectory during a grasp and t...
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ISBN:
(纸本)9781479932740
Grasping and twisting are basic motor skills for the execution of activities in daily life such as opening a door with a door knob. We study the relationship between grip force and hand trajectory during a grasp and twist task when unexpected load torques are encountered. The experimental results on grip force development and hand trajectories are consistent with similar studies on grasp and lift tasks in the literature. We also seek to build a simple model to study human feedforward control during grasp and twist movement. Our model includes a position source and driving point impedance. We provide detailed procedures to identify the relationship between the impedance values and grip forces and the algorithm to estimate the position source. We check our model by comparing the model prediction and experimental data on certain catch trial trajectories.
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