Niels van Duijkeren
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View article: Real-Time-Feasible Collision-Free Motion Planning For Ellipsoidal Objects
Real-Time-Feasible Collision-Free Motion Planning For Ellipsoidal Objects Open
Online planning of collision-free trajectories is a fundamental task for robotics and self-driving car applications. This paper revisits collision avoidance between ellipsoidal objects using differentiable constraints. Two ellipsoids do no…
View article: Stochastic Model Predictive Control with Optimal Linear Feedback for Mobile Robots in Dynamic Environments
Stochastic Model Predictive Control with Optimal Linear Feedback for Mobile Robots in Dynamic Environments Open
Robot navigation around humans can be a challenging problem since human movements are hard to predict. Stochastic model predictive control (MPC) can account for such uncertainties and approximately bound the probability of a collision to t…
View article: Stochastic Model Predictive Control with Optimal Linear Feedback for Mobile Robots in Dynamic Environments
Stochastic Model Predictive Control with Optimal Linear Feedback for Mobile Robots in Dynamic Environments Open
View article: Receding Horizon Re-Ordering of Multi-Agent Execution Schedules
Receding Horizon Re-Ordering of Multi-Agent Execution Schedules Open
The trajectory planning for a fleet of automated guided vehicles (AGVs) on a roadmap is commonly referred to as the multi-agent path finding (MAPF) problem, the solution to which dictates each AGV's spatial and temporal location until it r…
View article: Receding Horizon Re-ordering of Multi-Agent Execution Schedules
Receding Horizon Re-ordering of Multi-Agent Execution Schedules Open
The trajectory planning for a fleet of Automated Guided Vehicles (AGVs) on a roadmap is commonly referred to as the Multi-Agent Path Finding (MAPF) problem, the solution to which dictates each AGV's spatial and temporal location until it r…
View article: An Industrial Perspective on Multi-Agent Decision Making for Interoperable Robot Navigation following the VDA5050 Standard
An Industrial Perspective on Multi-Agent Decision Making for Interoperable Robot Navigation following the VDA5050 Standard Open
This paper provides a perspective on the literature and current challenges in Multi-Agent Systems for interoperable robot navigation in industry. The focus is on the multi-agent decision stack for Autonomous Mobile Robots operating in mixe…
View article: Collision-free Motion Planning for Mobile Robots by Zero-order Robust Optimization-based MPC
Collision-free Motion Planning for Mobile Robots by Zero-order Robust Optimization-based MPC Open
This paper presents an implementation of robust model predictive control (MPC) for collision-free reference trajectory tracking for mobile robots. The presented approach considers the robot motion to be subject to process noise bounded by …
View article: The e-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing
The e-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing Open
Robotic manipulation is currently undergoing a profound paradigm shift due to the increasing needs for flexible manufacturing systems, and at the same time, because of the advances in enabling technologies such as sensing, learning, optimi…
View article: The E-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing
The E-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing Open
View article: End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control Open
It is well-known that inverse dynamics models can improve tracking performance in robot control.These models need to precisely capture the robot dynamics, which consist of well-understood components, e.g., rigid body dynamics, and effects …
View article: End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control Open
It is well-known that inverse dynamics models can improve tracking performance in robot control. These models need to precisely capture the robot dynamics, which consist of well-understood components, e.g., rigid body dynamics, and effects…
View article: A caster-wheel-aware MPC-based motion planner for mobile robotics
A caster-wheel-aware MPC-based motion planner for mobile robotics Open
Differential drive mobile robots often use one or more caster wheels for\nbalance. Caster wheels are appreciated for their ability to turn in any\ndirection almost on the spot, allowing the robot to do the same and thereby\ngreatly simplif…
View article: acados—a modular open-source framework for fast embedded optimal control
acados—a modular open-source framework for fast embedded optimal control Open
View article: Learning Forceful Manipulation Skills from Multi-modal Human Demonstrations
Learning Forceful Manipulation Skills from Multi-modal Human Demonstrations Open
Learning from Demonstration (LfD) provides an intuitive and fast approach to program robotic manipulators. Task parameterized representations allow easy adaptation to new scenes and online observations. However, this approach has been limi…
View article: Action-Conditional Recurrent Kalman Networks For Forward and Inverse\n Dynamics Learning
Action-Conditional Recurrent Kalman Networks For Forward and Inverse\n Dynamics Learning Open
Estimating accurate forward and inverse dynamics models is a crucial\ncomponent of model-based control for sophisticated robots such as robots driven\nby hydraulics, artificial muscles, or robots dealing with different contact\nsituations.…
View article: A Feedback Scheme to Reorder a Multi-Agent Execution Schedule by Persistently Optimizing a Switchable Action Dependency Graph
A Feedback Scheme to Reorder a Multi-Agent Execution Schedule by Persistently Optimizing a Switchable Action Dependency Graph Open
In this paper we consider multiple Automated Guided Vehicles (AGVs) navigating a common workspace to fulfill various intralogistics tasks, typically formulated as the Multi-Agent Path Finding (MAPF) problem. To keep plan execution deadlock…
View article: Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning Open
Estimating accurate forward and inverse dynamics models is a crucial component of model-based control for sophisticated robots such as robots driven by hydraulics, artificial muscles, or robots dealing with different contact situations. An…
View article: acados: a modular open-source framework for fast embedded optimal\n control
acados: a modular open-source framework for fast embedded optimal\n control Open
This paper presents the acados software package, a collection of solvers for\nfast embedded optimization intended for fast embedded applications. Its\ninterfaces to higher-level languages make it useful for quickly designing an\noptimizati…
View article: Dual-Objective NMPC: Considering Economic Costs Near Manifolds
Dual-Objective NMPC: Considering Economic Costs Near Manifolds Open
This paper presents a dual-objective nonlinear model predictive control (NMPC) algorithm for stabilizing a target neighborhood of a state-space manifold of a nonlinear dynamical system and for concurrently optimizing an economic objective …
View article: Efficient Partial Condensing Algorithms for Nonlinear Model Predictive Control with Partial Sensitivity Update
Efficient Partial Condensing Algorithms for Nonlinear Model Predictive Control with Partial Sensitivity Update Open
In Nonlinear Model Predictive Control(NMPC), an optimal control problem (OCP) is solved repeatedly at every sampling instant. To satisfy the real-time restriction, modern methods tend to convert the OCP into structured Nonlinear Programmin…
View article: Towards a modular software package for embedded optimization
Towards a modular software package for embedded optimization Open
In this paper we present acados, a new software package for model predictive control. It provides a collection of embedded optimization algorithms written in C, with a strong focus on computational efficiency. Its modular structure makes i…
View article: Towards Dynamic Optimization with Partially Updated Sensitivities
Towards Dynamic Optimization with Partially Updated Sensitivities Open
In nonlinear model predictive control (NMPC), a control task is approached by repeatedly solving an optimal control problem (OCP) over a receding horizon. Popularly, the OCP is approximated with a finite-dimensional nonlinear program (NLP)…
View article: Low-cost Carry-home Mobile Platforms for Project-based Evaluation of Control Theory
Low-cost Carry-home Mobile Platforms for Project-based Evaluation of Control Theory Open
This paper presents mobile platforms that were recently designed in support of an introductory control course. Through dedicated assignments, the students are guided to implement and validate all parts of the course on a setup, ranging fro…
View article: Cartesian constrained time-optimal point-to-point motion planning for robots: the waiter problem
Cartesian constrained time-optimal point-to-point motion planning for robots: the waiter problem Open
Time-optimal point-to-point motion is of significant importance for maximizing the productivity of robot systems. This type of motion planning for robots is however a complex problem and is therefore often solved in two phases. First, a hi…
View article: Real-Time NMPC for Semi-Automated Highway Driving of Long Heavy Vehicle Combinations**The research leading to these results was partly funded by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013/ under REA grant agreement n° 607957. This work also benefits from Center-of-Excellence Optimization in Engineering (OPTEC), the Belgian Pro-gramme on Interuniversity Attraction Poles, initiated by the Bel- gian Federal Science Policy Office (DYSCO). The applied research on commercial heavy vehicles was funded by Volvo Group Trucks Technology (VGTT) and Virtual Prototyping Centre (ViP).
Real-Time NMPC for Semi-Automated Highway Driving of Long Heavy Vehicle Combinations**The research leading to these results was partly funded by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013/ under REA grant agreement n° 607957. This work also benefits from Center-of-Excellence Optimization in Engineering (OPTEC), the Belgian Pro-gramme on Interuniversity Attraction Poles, initiated by the Bel- gian Federal Science Policy Office (DYSCO). The applied research on commercial heavy vehicles was funded by Volvo Group Trucks Technology (VGTT) and Virtual Prototyping Centre (ViP). Open