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A catadioptric vision system combines a camera and a mirror to achieve a wide field of view imaging system. This type of vision system has many potential applications in mobile robotics. This paper is concerned with the design of a robust image-based control scheme using a catadioptric vision system mounted on a mobile robot. We exploit the fact that the(More)
This paper presents an approach for modeling user's driving-characteristics in a steering task, and determining the parameters of a virtual fixture to assist the user-control on the basis of his/her task-performances. First, we briefly introduce our assistive human-robot interaction (HRI) interface and a virtual fixture as backgrounds related to this(More)
Neurological disorders are the leading causes of poor balance. Previous studies have shown that biofeedback can compensate for weak or missing sensory information in people with sensory deficits. These biofeedback inputs can be easily recognized and converted into proper information by the central nervous system (CNS), which integrates the appropriate(More)
Falling accidents are costly due to their prevalence in the workplace. Slipping has been known to be the main cause of falling. Understanding the motor response used to regain balance after slipping is crucial to developing intervention strategies for effective recovery. Interestingly, studies on spinalized animals and studies on animals subjected to(More)
In this paper, we propose a novel system architecture and control scheme, a human-machine perceptual feedback system and control, to enhance a user's control performance while he is teleoperating a mobile robot with a joystick. First, we model the user, robot, and human-machine perceptual feedback controller. The two key roles of the controller are: a)(More)
This paper presents UAV(Unmanned Aerial Vehicle) simulation under artificial potential function. I set up a simulation environment with a UAV, an obstacle, and a goal object. The UAV was out to fly toward a goal object while navigating in a space where an obstacle was placed. In this simulation, I set up three control points: a head, a leaf wing, and a(More)
This paper presents Probabilistic Roadmap Method (PRM) simulation with straight-line local planner [1]. I set up a simulation environment with 7-links robot, obstacles (bombs), and a goal. First of all, I generated samples in free configuration space. Second, if one sample could be connected to its neighbor samples, store these two samples in a graph with a(More)
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