Research Objective: To develop offline-coordination planning techniques for multi-robot systems with partially shared workspaces that enables them to allocate and perform manufacturing tasks in a time-effective and computationally efficient manner.
Task Allocation and Dead-Lock-Free Trajectory Planning for Collaborative Multi-Robot System
Collaborative robots performing a manufacturing task
Mohammad Zainullah Khan
Advisors: Andrew Murray, Ph.D & David Myszka, Ph.D
Department of Mechanical & Aerospace Engineering
Robot 1
Robot 3
Robot 2
Divide task into raster segments
Allocate rasters to each robot using Tabu Search Heuristic
Perform Combinatory Collision checking
Introduce delays
Resolve Deadlocks
Path Modification
Task-time calculation
Tabu Search Heuristic
Tabu Search Heuristic is employed for task allocation and to find the local optimal path with minimum timespan.
Combinatory Collision Checking
Generally, for m robots, each with n links:
Future Work
The coordination planning techniques now need to be implemented on a 5/6 DOF multi-robot systems for manufacturing environment.
Applications
Modeling of three 3P robots in MATLAB
Collision�Checks
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Reference:�https://www.therobotreport.com/top-5-countries-using-industrial-robots-2018/
Research Objective: To develop offline-coordination planning techniques for multi-robot systems with partially shared workspaces that enables them to allocate and perform manufacturing tasks in a time-effective and computationally efficient manner.
Task Allocation and Dead-Lock-Free Trajectory Planning for Collaborative Multi-Robot System
Modeling of three 3P robots in MATLAB
Collaborative robots performing a manufacturing task
Mohammad Zainullah Khan
Advisors: Andrew Murray, Ph.D & David Myszka, Ph.D
Department of Mechanical & Aerospace Engineering
Robot 1
Robot 3
Robot 2
Divide task into raster segments
Allocate rasters to each robot using Tabu Search Heuristic
Go through the robots’ motion
Perform Combinatory Collision checking
Collisions Detected?
Introduce delays iteratively in every robot’s path to resolve collisions
Select the minimum delay
Check for deadlocks
Iteratively modify each robot’s path to resolve deadlock
Select path modification leading to minimum increase in task time
Restart collision checking from start
Generate a matrix of each robot’s end-effector and time
Calculates the task-time
Animates the robots
Flowchart for Offline Path Planning with task-allocation, collision avoidance & deadlock resolution
Tabu Search Heuristic
Tabu Search Heuristic is employed for task allocation and to find the local optimal path with minimum timespan.
Combinatory Collision Checking
Generally, for m robots, each with n links:
Research Objective: To develop offline-coordination planning techniques for multi-robot systems with partially shared workspaces that enables them to allocate and perform manufacturing tasks in a time-effective and computationally efficient manner.
Applications
Simplified Problem
Two DOF cranes collaborating to arrange boxes in a specific order
References
“Performance of Collaborative Robot Systems.”NIST,8 May 2018, https://www.nist.gov/programs-projects /performance-collaborative-robot-systems.
Hieu Bui, Harry A. Pierson, Sarah Nurre Pinkley & Kelly M. Sullivan (2021) Toolpath planning for multi-gantry additive manufacturing, IISE Transactions, 53:5, 552-567, DOI: 10.1080/24725854.2020.1775915
Task Allocation and Dead-Lock-Free Trajectory Planning for Collaborative Multi-Robot System
Task Allocation & Path Planning
Tabu Search Heuristic is employed for task allocation and to find the optimal path with minimum timespan.
Optimal Path with collisions
Collision Avoidance
In order to avoid collisions, delays are introduced in either crane 1 or crane 2’s path (which ever results in lower timespan).
Pick and arrange four boxes using two cranes in the optimum manner without collisions.
Three collaborative robots performing a manufacturing task
Mohammad Zainullah Khan
Advisors: Andrew Murray, Ph.D & David Myszka, Ph.D
Department of Mechanical & Aerospace Engineering
3rd robot introduced
3rd Robot’s lengths & attachment point defined
3rd robot drawn
Incorporate Robot motion
Include in Tabu Search Heuristic
Perform Combinatory Collision Checking
Introduce delays to resolve collisions
Check for any deadlocks
Resolve Deadlocks
Make Time-vs-Coordinates matrix
Show collaborative motion
Robot 1
Robot 3
Robot 2