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Robots often have limited knowledge about the environment and need to continuously acquire new knowledge in order to collaborate with the humans. To address this issue, this paper presents a method which allows the human to teach a robot new object types and attributes through natural language (NL) instructions. A simple yet robust vision algorithm is proposed to segment objects and describe the relations...
This paper presents a navigation algorithm based on traversability for search and rescue robot. The traversability includes pre-traversability and real-time traversability. The pre-traversability is calculated using terrain roughness and roll and pitch change. The terrain roughness is based on the texture information from the image captured by the on-board camera. An artificial neural network has...
Controlling robots with natural language enables untrained users to interact with them more easily. A significant challenge for such systems is the mismatched visual perceptual capabilities between humans and robots. Most existing methods try to improve the perceptual ability of robots by either developing robust vision algorithms to describe and identify objects more accurately, or refining the object...
Shaft orbit plays an important role in condition monitoring and fault diagnosis for hydropower unit. A novel method of shaft orbit identification based on low-level image feature representation and classification is proposed. The main characteristic is that the vibrations of the shaft in terms of displacements are used to draw points in an image panel at a fixed scale, resulting in the shaft orbit...
A novel method of dynamic hand gesture recognition based on Speeded Up Robust Features (SURF) tracking is proposed. The main characteristic is that the dominant movement direction of matched SURF points in adjacent frames is used to help describing a hand trajectory without detecting and segmenting the hand region. The dynamic hand gesture is then modeled by a series of trajectory direction data streams...
This paper focuses on the development of a multi-agent based robot telesupervision architecture for hazardous materials detection. By combining the supervisors' advanced reasoning capabilities with the robots' local autonomous capacities, this architecture is designed to maximize the safety and efficiency of robot supervisors to detect and deal with hazardous materials. The multi-agent framework not...
Several key issues about the teleoperation system for semi-autonomous reconnaissance robot have been addressed. A human-robot collaborative semi-autonomous mobile robot architecture (SAMRA) which combine the complementary capabilities of both robot's local autonomy and human intelligence is proposed firstly. Then, a novel autonomous mission executive mechanism based on macro behavior and a hybrid...
In the research of reconnaissance robot to respond events involving hazardous materials, a novel hybrid behavior coordination mechanism based on priority and FSA is proposed. It uses a behavior group which combines several elementary behaviors based on priority to perform simple scout tasks. And then uses one of specified FSAs designed for each more complex task respectively as the behavior group...
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