6533b874fe1ef96bd12d643c

RESEARCH PRODUCT

Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study

Jörn MehnenCarmelo MineoJaime ZabalzaErfu YangQuang-cuong PhamCuebong WongZixiang FeiJinchang RenYijun YanTony Rodden

subject

0209 industrial biotechnologyComputer scienceMachine visionTKReal-time computingRobot manipulator02 engineering and technologyWorkspaceAdaptive Reasoninglcsh:Chemical technologyBiochemistryHuman–robot interactionArticleAnalytical ChemistrySettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchinehuman-robot interaction020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringlcsh:TP1-1185Motion planningElectrical and Electronic EngineeringInstrumentationpath planningCollision avoidancerobot controlsmart sensingAdaptive reasoningdynamic environmentsAtomic and Molecular Physics and OpticsRobot control:Engineering::Mechanical engineering [DRNTU]ObstacleDynamic EnvironmentsRobot020201 artificial intelligence & image processingadaptive reasoning

description

Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a case study in which a robotic manipulator, namely a KUKA KR90 R3100, is provided with smart sensing capabilities such as vision and adaptive reasoning for real-time collision avoidance and online path planning in dynamically-changing environments. A machine vision module based on low-cost cameras and color detection in the hue, saturation, value (HSV) space is developed to make the robot aware of its changing environment. Therefore, this vision allows the detection and localization of a randomly moving obstacle. Path correction to avoid collision avoidance for such obstacles with robotic manipulator is achieved by exploiting an adaptive path planning module along with a dedicated robot control module, where the three modules run simultaneously. These sensing/smart capabilities allow the smooth interactions between the robot and its dynamic environment, where the robot needs to react to dynamic changes through autonomous thinking and reasoning with the reaction times below the average human reaction time. The experimental results demonstrate that effective human-robot and robot-robot interactions can be realized through the innovative integration of emerging sensing techniques, efficient planning algorithms and systematic designs. Published version

10.3390/s19061354https://hdl.handle.net/10356/105930