A Framework for Hybrid Cells That Support Safe and Efficient Human-Robot Collaboration in Assembly Operations

2014 ◽  
Author(s):  
Carlos W. Morato ◽  
Krishnanand N. Kaipa ◽  
Jiashun Liu ◽  
Satyandra K. Gupta
Keyword(s):  
Human Model ◽  
System State ◽  
Hybrid Cells ◽  
Generation System ◽  
State Monitoring ◽  
Virtual Cell ◽  
Plan Generation ◽  
Collaboration Model ◽  
Assembly Operations ◽  
Human Robot Collaboration

In this paper, we present a framework to build hybrid cells that support safe and efficient human-robot collaboration during assembly operations. Our approach considers a representative one-robot one-human model in which a human and a robot asynchronously work toward assembling a product. Whereas the human retrieves parts from a bin and brings them into the robot workspace, the robot picks up parts from its workspace and assembles them into the product. Using this collaboration model, we explicate the design details of the overall framework comprising three modules — plan generation, system state monitoring, and contingency handling. We provide details of the virtual cell and the physical cell used to implement our framework. Finally, we report results from human-robot collaboration experiments to illustrate our approach.

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

2018 ◽  
Vol 18 (3) ◽  
Author(s):  
Krishnanand N. Kaipa ◽  
Carlos W. Morato ◽  
Satyandra K. Gupta
Keyword(s):  
Three Dimensional ◽  
System State ◽  
Hybrid Cells ◽  
Generation System ◽  
State Monitoring ◽  
Plan Generation ◽  
3D Printed ◽  
Assembly Operations ◽  
Human Robot Collaboration

This paper presents a framework to build hybrid cells that support safe and efficient human–robot collaboration during assembly operations. Our approach allows asynchronous collaborations between human and robot. The human retrieves parts from a bin and places them in the robot's workspace, while the robot picks up the placed parts and assembles them into the product. We present the design details of the overall framework comprising three modules—plan generation, system state monitoring, and contingency handling. We describe system state monitoring and present a characterization of the part tracking algorithm. We report results from human–robot collaboration experiments using a KUKA robot and a three-dimensional (3D)-printed mockup of a simplified jet-engine assembly to illustrate our approach.

System State Monitoring to Facilitate Safe and Efficient Human-Robot Collaboration in Hybrid Assembly Cells

2017 ◽  
Author(s):  
Carlos W. Morato ◽  
Krishnanand N. Kaipa ◽  
Satyandra K. Gupta
Keyword(s):  
Hybrid Cell ◽  
System State ◽  
Hybrid Assembly ◽  
State Monitoring ◽  
Matching Algorithm ◽  
Plan Generation ◽  
3D Printed ◽  
Assembly Tasks ◽  
Human Robot Collaboration

Hybrid assembly cells allow humans and robots to collaborate on assembly tasks. We consider a model of the hybrid cell in which a human and a robot asynchronously collaborate to assemble a product. The human retrieves parts from a bin and places them in the robot’s workspace, while the robot picks up the placed parts and assembles them into the product. Realizing hybrid cells requires -automated plan generation, system state monitoring, and contingency handling. In this paper we describe system state monitoring and present a characterization of the part matching algorithm. Finally, we report results from human-robot collaboration experiments using a KUKA robot and a 3D-printed mockup of a simplified jet-engine assembly to illustrate our approach.

TEMPERATURE MODELS FOR GRINDING SYSTEM STATE MONITORING

2019 ◽  
Vol 2 (3) ◽  
pp. 216-229
Author(s):  
Vasily Larshin ◽  
Natalia Lishchenko
Keyword(s):  
System State ◽  
State Monitoring ◽  
Grinding System

Instruction Generation for Assembly Operations Performed by Humans

2012 ◽  
Author(s):  
Krishnanand Kaipa ◽  
Carlos Morato ◽  
Boxuan Zhao ◽  
Satyandra K. Gupta
Keyword(s):  
Motion Planning ◽  
Free Path ◽  
Generation System ◽  
Complex Assembly ◽  
Learning Time ◽  
Design Changes ◽  
Multimodal Information ◽  
Information Text ◽  
Assembly Operations

This paper presents the design of an instruction generation system that can be used to automatically generate instructions for complex assembly operations performed by humans on factory shop floors. Multimodal information—text, graphical annotations, and 3D animations—is used to create easy-to-follow instructions. This thereby reduces learning time and eliminates the possibility of assembly errors. An automated motion planning subsystem computes a collision-free path for each part from its initial posture in a crowded scene onto its final posture in the current subassembly. Visualization of this computed motion results in generation of 3D animations. The system also consists of an automated part identification module that enables the human to identify, and pick, the correct part from a set of similar looking parts. The system’s ability to automatically translate assembly plans into instructions enables a significant reduction in the time taken to generate instructions and update them in response to design changes.

Damaged Ship Anti-Flooding Decision Plan Intelligent Generation System Based on Petri Net and Heuristic Color Genetic Algorithm

2013 ◽  
Vol 706-708 ◽  
pp. 1866-1870
Author(s):  
Ang Li ◽  
Jin Yun Pu
Keyword(s):  
Genetic Algorithm ◽  
Petri Net ◽  
Search Efficiency ◽  
Generation System ◽  
Plan Generation ◽  
Intelligent Decision ◽  
Balance Decision ◽  
Definition Of ◽  
Algorithm Search ◽  
Damaged Ship

No matter in the wartime or in the peace time, the intelligent generation system of damaged ship anti-flooding decision plan is an important tool to guarantee ship survivability and safety. The intelligent decision plan generation system which has high search efficiency plays an important role in recovering the buoyancy and stability indicts of damaged ship. The intelligent decision plan generation system introduced in this paper contains Petri net model and heuristic color genetic algorithm. The Petri net is used to model the ship anti-flooding decision process and the heuristic color genetic algorithm is used to solve intelligent hull balance decision problem. The traditional genetic algorithm is improved according to the special demand of hull balance. Based on the definition of the colored gene and the foundation of the heuristic search rules, the heuristic color genetic algorithm is given to improve the traditional genetic algorithm search efficiency.

Active distribution system state estimation incorporating photovoltaic generation system model

2020 ◽  
Vol 182 ◽  
pp. 106247
Author(s):  
Zhi Fang ◽  
Yuzhang Lin ◽  
Shaojian Song ◽  
Chunning Song ◽  
Xiaofeng Lin ◽  
...  
Keyword(s):  
State Estimation ◽  
Distribution System ◽  
System Model ◽  
System State ◽  
Generation System ◽  
Photovoltaic Generation ◽  
Active Distribution System

scholarly journals Human Body Simulation Within a Hybrid Operating Method for a Safe and Efficient Human-Robot Collaboration

2022 ◽  
pp. 191-202
Author(s):  
Kai Lemmerz ◽  
Bernd Kuhlenötter
Keyword(s):  
Production Systems ◽  
Separation Distance ◽  
Human Motion ◽  
Physical Contact ◽  
Human Model ◽  
Body Contact ◽  
Digital Human Model ◽  
Body Regions ◽  
And Performance ◽  
Human Robot Collaboration

AbstractThe planning and integration of production systems with a direct human-robot collaboration (HRC) is still associated with various technical challenges. This applies especially to the realization of the operation methods speed and separation monitoring (SSM) as well as power and force limiting (PFL). Due to the limited consideration of the human motion behaviour, the required dynamic separation distance in SSM is frequently oversized in practice. The main consequences are wasted space as well as cycle time and performance losses within the corresponding HRC application. In PFL a physical contact between the operator and robot is permissible, taking into account specified biomechanical thresholds. However, there is still a lack of suitable use-cases since the maximum permissible speeds are on a very low level. Moreover some thresholds regarding the transient contact case are still non-applicable for critical body areas (e.g. temple, middle of forehead). The study of this paper is related to a kinematic state determination of the human operator within a new hybrid collaborative operation. In this method the SSM type is extended regarding the description of the operator and coupled with the two-body contact model of the PFL. Using a planning and simulation tool for HRC, the kinematic states of different body regions are derived from an integrated and parameterized digital human model. Afterwards, these body regions are mapped to the characteristic body areas of the ISO/TS 15066, whereby the resulting information will be applied in an adaptive robot speed control. The performance of the presented concept will be evaluated using an exemplary simulated HRC scenario.

scholarly journals Herding the Crowd: Using Automated Planning for Better Crowdsourced Planning

2017 ◽  
Vol 4 (1) ◽  
pp. 25-46
Author(s):  
Lydia Manikonda ◽  
Tathagata Chakraborti ◽  
Kartik Talamadupula ◽  
Subbarao Kambhampati
Keyword(s):  
Automated Planning ◽  
Human Computation ◽  
Generation System ◽  
Planning And Scheduling ◽  
Plan Generation ◽  
Tour Planning ◽  
Primitive Forms ◽  
Preference Models ◽  
Conference Scheduling

One subclass of human computation applications are those directed at tasks that involve planning (e.g. tour planning) and scheduling (e.g. conference scheduling). Interestingly, work on these systems shows that even primitive forms of automated oversight on the human contributors helps in significantly improving the effectiveness of the humans/crowd. In this paper, we argue that the automated oversight used in these systems can be viewed as a primitive automated planner, and that there are several opportunities for more sophisticated automated planning in effectively steering crowdsourced planning. Straightforward adaptation of current planning technology is however hampered by the mismatch between the capabilities of human workers and automated planners. We identify and partially address two important challenges that need to be overcome before such adaptation of planning technology can occur: (i) interpreting inputs of the human workers (and the requester) and (ii) steering or critiquing plans produced by the human workers, armed only with incomplete domain and preference models. To these ends, we describe the implementation of AI-MIX, a tour plan generation system that uses automated checks and alerts to improve the quality of plans created by human workers.

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