60 citations · 85 across the 11 of their papers we have counts for
11 papers
Critical slowing down for predicting controller induced loss of control in quadrotors
Jasper J. van Beers, Prashant Solanki, Erik-Jan van Kampen +1
We develop a novel forecasting scheme to anticipate controller induced loss of control (LOC) in quadrotors and evaluate it on real LOC flight data from four different quadrotors. F…
Reachability-Preserving Bellman Operator for the Discounted Reach-Cost Value Function: Uniting Hamilton-Jacobi Reachability and Reinforcement Learning
Isabelle El-Hajj, Prashant Solanki, Jasper van Beers +2
Hamilton-Jacobi (HJ) reachability provides rigorous safety and reachability guarantees for continuous-time dynamical systems, but its numerical solution suffers from the curse of d…
Unifying Hamilton-Jacobi Reachability and Reinforcement Learning
Prashant Solanki, Isabelle El-Hajj, Jasper van Beers +2
We unify Hamilton-Jacobi (HJ) reachability and Reinforcement Learning (RL) through a proposed running cost formulation. We prove that the resultant travel-cost value function is th…
Action-Increment-Constrained Policy Optimization for Smooth Online Adaptive Critic Flight Control with Actuator Rate Constraints and Low Computational Complexity (extended version with Ultimate Uniform Boundedness analysis)
Yifei Li, Erik-Jan van Kampen
Approximate Dynamic Programming (ADP) enables online control-law adaptation through adaptive critic methods. A safety challenge in applying ADP to angle-of-attack (AoA) tracking co…
Deep deterministic policy gradient with symmetric data augmentation for lateral attitude tracking control of a fixed-wing aircraft
Yifei Li, Erik-Jan van Kampen
The symmetry of dynamical systems can be exploited for state-transition prediction and to facilitate control policy optimization. This paper leverages system symmetry to develop sa…
Adaptive Risk-Tendency: Nano Drone Navigation in Cluttered Environments with Distributional Reinforcement Learning
Cheng Liu, Erik-Jan van Kampen, Guido C. H. E. de Croon
Enabling the capability of assessing risk and making risk-aware decisions is essential to applying reinforcement learning to safety-critical robots like drones. In this paper, we i…
Soft Actor-Critic Deep Reinforcement Learning for Fault Tolerant Flight Control
Killian Dally, Erik-Jan van Kampen
Fault-tolerant flight control faces challenges, as developing a model-based controller for each unexpected failure is unrealistic, and online learning methods can handle limited sy…
Adaptive Control Strategy for Constant Optical Flow Divergence Landing
H. W. Ho, G. C. H. E. de Croon, E. van Kampen +2
Bio-inspired methods can provide efficient solutions to perform autonomous landing for Micro Air Vehicles (MAVs). Flying insects such as honeybees perform vertical landings by keep…
On Approximate Dynamic Programming with Multivariate Splines for Adaptive Control
Willem Eerland, Coen de Visser, Erik-Jan van Kampen
We define a SDP framework based on the RLSTD algorithm and multivariate simplex B-splines. We introduce a local forget factor capable of preserving the continuity of the simplex sp…
Framework for state and unknown input estimation of linear time-varying systems
Peng Lu, Erik-Jan van Kampen, Cornelis C. de Visser +1
The design of unknown-input decoupled observers and filters requires the assumption of an existence condition in the literature. This paper addresses an unknown input filtering pro…
Towards the multivariate simplotope spline: continuity conditions in a class of mixed simplotopic grids
Tim Visser, Cornelis C. de Visser, Erik-Jan van Kampen
Smooth joins of simplex Bernstein-Bézier polynomials have been studied extensively in the past. In this paper a new method is proposed to define continuity conditions for tensor-pr…