Safe Human Robot Interaction by Using Exteroceptive Sensing Based Human Modeling

Abstract

In this paper, we propose an exteroceptive sensing based framework to achieve safe human-robot interaction during shared tasks. Our approach allows a human to operate in close proximity with the robot, while pausing the robot’s motion whenever a collision between the human and the robot is imminent. The human’s presence is sensed by a N-range sensor based system, which consists of multiple range sensors mounted at various points on the periphery of the work cell. Each range sensor is based on a Microsoft Kinect sensor. Each sensor observes the human and outputs a 20 DOF human model. Positional data of these models are fused together to generate a refined human model. Next, the robot and the human model are approximated by dynamic bounding spheres and the robot’s motion is controlled by tracking the collisions between these spheres. Whereas most previous exteroceptive methods relied on depth data from camera images, our approach is one of the first successful attempts to build an explicit human model online and use it to evaluate human-robot interference. Real-time behavior observed during experiments with a 5 DOF robot and a human safely performing shared assembly tasks validate our approach.

Human-robot collision predictor for flexible assembly

“…In this paper, the latter has been developed as part of a PREdictor of Human-RObot COllision (PREHUROCO) framework. The subject of the prediction in this case is the predetermined movement of the robot, which can be recorded and will occur after a certain time, so a similar framework had to be created to that described in [10]. However, instead of a digital twin of the robot (real-time 3D visualisation of the robot), a pre-played robot model motion was used together with the 3D skeleton model of the operator.…”

“…However, these approaches are all manifested in robot control parameter modification rather than in operator warnings. Both the above studies refer to the work of Carlos Morato et al [10], who presented a similar solution by creating a framework using multiple Kinects to generate a 3D model with bounding spheres for human movements in real time. The proposed framework calculates human-robot interference in a 3D space with a physics-based simulation engine.…”

Design of Hybrid Cells to Facilitate Safe and Efficient Human–Robot Collaboration During Assembly Operations

“…We assume that the robot will be able to execute motion commands given to it, so that the assembly cell will know the state of the robot. A human tracking system was developed in our previous works [1,11] by using multiple Microsoft-Kinect sensors. The system is capable of building an explicit model of the human in near real time.…”

“…Our approach to ensuring safety in the hybrid cell is based on the precollision strategy developed in Ref. [11]: robot's pauses to move whenever an imminent collision between the human and the robot is detected. This is a simpler bi-modal strategy, in which the robot directly changes from clear to pause when the estimated distance is below a threshold.…”

“…More system-level comparative results are outside the scope of this paper. Recent advances in safer industrial robots [8][9][10] and exteroceptive safety systems [1,11] create a potential for hybrid cells where humans and robots can work side-by-side, without being separated from each other by physical cages. However, realizing this goal is challenging.…”