Selective Visual and Tactile Sensing for Autonomous Systems Perception and Robotic Applications

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The development of autonomous robotic systems represents a strategic undertaking for developed countries around the world, including in Canada, to protect populations, ensure proper health care and personal services, provide competitive advantage to the manufacturing industry, and sustain economic prosperity. However, the most advanced technologies still face limitations in their sensing and perception capability. Among the challenges encountered, the acquisition of large amounts of data quickly leads to saturated processing capabilities that preempt full usage of the information available for autonomous systems to make educated decisions. Nevertheless, a recent trend has emerged that aims at merging measurements from vision, force and tactile sensors to develop systems capable of performing dexterous manipulation, in an attempt to get closer to human capabilities.****The proposed research focuses on the development of selective but accurate sensing methods combining machine vision and tactile probing to support autonomous decision systems in advanced robotic applications. Selective sensing is defined as intelligently selecting where to next acquire information from, based upon previously acquired knowledge of the same scene, with the goal to minimize the total amount of data required to understand the scene. As a result, selective sensing orients the collection of information over regions that are of strategic importance for the success, safety and robustness of a robotic operation.***The main objective is to develop integrated perceptual robotic approaches that combine visual and tactile perception to detect, selectively measure, model and interpret a complex environment composed of objects of a priori unknown nature and physical properties. The understanding of the scene made available will then support the operation of a mobile robot, or a robot arm/hand, to further selectively probe, or interact with the objects found.***More specifically, formal selective 3D imaging methods will be expanded to support acquisition of data from multiple viewpoints, and to integrate different sensing modalities and perform data fusion from color and thermal imaging, depth, and tactile data. The research will also investigate bio-inspired image and signal processing methods to achieve efficient selective sensing, and finally, original adaptive compliant control schemes with be developed to support dexterous robotic interaction with either static, mobile, rigid or deformable objects under selective multi-modal sensory feedback.***The research will make major contributions on fundamental concepts and technological innovations for intelligent sensing and autonomous systems that are vital to critical robotic applications, such as assistive robotic systems, intelligent manufacturing, as well as security and hazardous material manipulation.**