activity
20152020
most citedKalman Filter Tuning with Bayesian Optimization

10 citations · 15 across the 4 of their papers we have counts for

collaborators

6 papers

cs.RO2020

Better Together: Online Probabilistic Clique Change Detection in 3D Landmark-Based Maps

Samuel Bateman, Kyle Harlow, Christoffer Heckman

Many modern simultaneous localization and mapping (SLAM) techniques rely on sparse landmark-based maps due to their real-time performance. However, these techniques frequently asse…

eess.SY201910 cited

Kalman Filter Tuning with Bayesian Optimization

Zhaozhong Chen, Nisar Ahmed, Simon Julier +1

Many state estimation algorithms must be tuned given the state space process and observation models, the process and observation noise parameters must be chosen. Conventional tunin…

cs.RO2019

FastCal: Robust Online Self-Calibration for Robotic Systems

Fernando Nobre, Christoffer Heckman

We propose a solution for sensor extrinsic self-calibration with very low time complexity, competitive accuracy and graceful handling of often-avoided corner cases: drift in calibr…

cs.RO2017

Materials that make robots smart

Nikolaus Correll, Christoffer Heckman

We posit that embodied artificial intelligence is not only a computational, but also a materials problem. While the importance of material and structural properties in the control…

cs.CV20173 cited

Hidden Markov Random Field Iterative Closest Point

John Stechschulte, Christoffer Heckman

When registering point clouds resolved from an underlying 2-D pixel structure, such as those resulting from structured light and flash LiDAR sensors, or stereo reconstruction, it i…

nlin.PS20152 cited

Pattern-Acquisition in Finite, Heterogenous, Delay-Coupled Swarms

Klimka Szwaykowska, Christoffer Heckman, Luis Mier-y-Teran-Romero +1

The self-organizing behavior of swarms of inter- acting particles or agents is a topic of intense research in fields extending from biology to physics and robotics. In this paper,…