Enhancing robotic agents through tactile perception and multi-modal interfaces

点击翻译按钮获取中文摘要

Traditional industrial robots are equipped with highly specialized sensing, perception, and actuation suites tailored to repeat a limited set of carefully scripted assembly and manufacturing operations. Nowadays, the application of robotic agents is expanding out of the production lines and advancing towards collaborating activities, interacting with other robots, and assisting humans. These agents have the ability to explore unstructured environments while simultaneously localizing themselves, mapping their surroundings, walking and interacting with people, but they still lack the dexterity required to handle even simple objects. Unfortunately, the capabilities that make robotic agents successful on factory lines are not sufficient in unstructured settings like homes, schools, and hospitals. Applications such as health and eldercare or that take place in hazardous or high-risk environments require robotic agents to be able to complete complex dexterous manipulation operations. To perform such activities, these agents must be able to handle various objects of different materials that can be situated out of the field of view of the robot or partially obstructed by the environment or by the robot itself. Identifying and constructing models for non-occluded objects is primarily accomplished using image processing, computer vision, and machine learning methods. On the other hand, objects in cluttered environments or partially occluded during in-hand manipulation may be identified, modeled and dexterously manipulated only by agents employing tactile perception strategies. In the long term, this research program aims at developing novel tactile perception methods for the manipulation, identification, classification, and modeling of heterogeneous objects, as well as the encoding and communication of tactile information. The proposed research program also contemplates the integration of other perceptual modalities such as computer vision, myoelectric signals, and gesture recognition into collaborative and assistive robotic agents. New theoretical results will be generated with a range of applications in mind, varying from virtual and virtualized reality, human-machine interfaces and telemanipulation to smart prostheses. The results of this research program will provide solutions for practical problems in the health and industrial sectors and will help develop close research collaborations between academia and industry. A total of six graduate and five undergraduate students will be trained with the support of this grant over the next five years, contributing to Canada's highly qualified personnel. The research findings enabled by the program will be disseminated in leading refereed journals and presented at international conferences of the field.