CIAO⁎: MPC-based Safe Motion Planning in Predictable Dynamic Environments

Schoels, Tobias; Rutquist, Per; Palmieri, Luigi; Zanelli, Andrea; Arras, Kai O.; Diehl, Moritz

doi:10.1016/j.ifacol.2020.12.072

Cited by 26 publications

(9 citation statements)

References 17 publications

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“…This subset excludes all states where a collision might occur and needs to be determined a priori. This method was applied by Liu et al [27] and Schoels et al [28] for trajectory generation of a mobile robot, where Schoels et al [28] approximated the collision-free subset by circles and Liu et al [27] used polyhedra at the current state. Rösmann et al [29] used a global planner to optimize trajectories of multiple mobile robots maneuvering in a low dimensional space.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

et al. 2022

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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.

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Section: Related Workmentioning

confidence: 99%

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

et al. 2022

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“…, where r m is the position of the m-th obstacle's CO, M m = diag{ 1 /(am+dsafe) 2 , 1 /(bm+dsafe) 2 } ∈ R 2×2 , and a m , b m define the ellipse's major and minor axis length, respectively 5 . This formulation can be translated directly into the obstacle constraint defined by (14d), i.e.,…”

Section: ) Ellipsoidal Formulation: An Ellipsoidal Obstacle Can Be Re...mentioning

confidence: 99%

“…with an additional safety distance d safe ∈ R. In this context, several contributions have been made following different approaches, see, e.g., [5], [6], [7]. The work [5] is concerned with finding a convex inner approximation of the signed distance and a so-called action radius of a controlled robot and lays focus on kinodynamic constraints. In [6] a linearization of the signed distance function is used but approximation errors can lead to numerical difficulties.…”

Section: Introductionmentioning

confidence: 99%

On the Dual Implementation of Collision-Avoidance Constraints in Path-Following MPC for Underactuated Surface Vessels

Helling

Roduner

Meurer

2021

2021 American Control Conference (ACC)

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A path-following collision-avoidance model predictive control (MPC) method is proposed which approximates obstacle shapes as convex polygons. Collision-avoidance is ensured by means of the signed distance function which is calculated efficiently as part of the MPC problem by making use of a dual formulation. The overall MPC problem can be solved by standard nonlinear programming (NLP) solvers. The dual signed distance formulation yields, besides the (dual) collisionavoidance constraints, norm, and consistency constraints. A novel approach is presented that combines the arising norm equality with the dual collision-avoidance inequality constraints to yield an alternative formulation reduced in complexity. Moving obstacles are considered using separate convex sets of linearly predicted obstacle positions in the dual problem. The theoretical findings and simplifications are compared with the often-used ellipsoidal obstacle formulation and are analyzed with regard to efficiency by the example of a simulated path-following autonomous surface vessel during a realistic maneuver and AIS obstacle data from the Kiel bay area.

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“…This subset excludes all states where a collision might occur and needs to be determined a priori. This method was applied by Liu et al [17] and Schoels et al [18] for trajectory generation of a mobile robot, where Schoels et al [18] approximated the collision free subset by circles and Liu et al [17] used polyhedra at the current state. Rösmann et al [19] uses a global planner to optimize trajectories of multiple mobile robots.…”

Section: Related Workmentioning

confidence: 99%

Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game

Gafur¹,

Kanagalingam²,

Ruskowski³

2021

Preprint

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A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance. In this work, we propose a real-time capable motion control algorithm, based on non-linear model predictive control, which accounts for static and dynamic collision avoidance. The proposed algorithm is formulated as a non-cooperative game, where each robot is considered as an agent. Each agent optimizes its own motion and accounts for the predicted movement of surrounding agents. We propose a novel approach to formulate the dynamic collision constraints. Additionally, we account for deadlocks that might occur in a setup of multiple robotic manipulators. We validate our algorithm on a pick and place scenario for four collaborative robots operating in a common workspace in the simulation environment Gazebo. The robots are controlled by the Robot Operating System (ROS). We demonstrate, that our approach is real-time capable and, due to the distributed nature of the approach, easily scales to an arbitrary number of robot manipulators in a shared workspace.

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CIAO⁎: MPC-based Safe Motion Planning in Predictable Dynamic Environments

Cited by 26 publications

References 17 publications

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

On the Dual Implementation of Collision-Avoidance Constraints in Path-Following MPC for Underactuated Surface Vessels

Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game

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