Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

Abstract

A flexible operation of multiple robotic manipulators operating in a dynamic environment requires online trajectory planning to ensure collision-free trajectories. In this work, we propose a real-time capable motion control algorithm, based on nonlinear model predictive control, which accounts for static and dynamic obstacles. The proposed algorithm is realized in a distributed scheme, where each robot optimizes its own trajectory with respect to the related objective and constraints. We propose a novel approach for collision avoidance between multiple robotic manipulators, where each robot accounts for the predicted movement of the neighboring robots. Additionally, we propose a method to reliably detect and resolve deadlocks occurring in a setup of multiple robotic manipulators. We validate our approach on pick and place scenarios involving multiple robotic manipulators operating in a common workspace in a realistic simulation environment set up in Gazebo. The robots are controlled using the Robot Operating System. Our approach scales up to 4 manipulators and computes a path for each robot in a simultaneous pick and place operation in 94% of all investigated cases without deadlock detection and 100 % of cases with the proposed deadlock resolution algorithm. In contrast, the investigated conventional path planners, such as PRM, PRM*, CHOMP and RRT-Connect, successfully plan a trajectory in at most 54% of all investigated cases for a simultaneous operation of 4 robotic manipulators hindering their application in setups of multiple manipulators.INDEX TERMS Robotic manipulators, collision avoidance, distributed model predictive control, motion control, deadlock, ROS.

Multi-Arm Trajectory Planning for Optimal Collision-Free Pick-and-Place Operations

“…The provided solution is feasible for certain production processes where the number of pieces to manipulate is small (less than 10 elements). Secondly, the movements that the robots must perform are constrained within a grid, which is less natural compared to other solutions such as [15], although it provides a robust and faster industrial solution to the problem. Lastly, a preliminary study using RobotStudio ® is required to create a database, including information about collision situations between arms.…”

“…These operations involve pure vertical moves and gripper open or close actions. In order to ensure a successful operation, the configuration of the robot places the gripper pointing towards the piece and the pieces have been defined as cubic blocks, just as it was done in [15].…”

Posicionamiento de ayuda visual utilizando compresión de nube de puntos y cámaras RGB-D para manipuladores robóticos

“…Entre las aplicaciones actuales más sobresalientes de los manipuladores robóticos están la fabricación de vehículos, manufacturación aditiva, agricultura de precisión [7], [8] e industria eléctrica [1], [2], [9]. Actualmente, el posicionamiento de los manipuladores robóticos se realiza mediante sensores inerciales, tales como IMU y enconder, que se encargan determinar la orientación del robot, cámaras visuales con imágenes RGB, sensores LIDAR [10]- [12], entre otros. Por otro lado, el uso de cámaras que permiten determinar la pose de diferentes objetos en entornos variados ha permitido la penetración de estas tecnologías a nivel industrial [13]- [17].…”