87 citations · 275 across the 25 of their papers we have counts for
19 papers · 1 filter
A Population-Level Analysis of Neural Dynamics in Robust Legged Robots
Eugene R. Rush, Christoffer Heckman, Kaushik Jayaram +1
Recurrent neural network-based reinforcement learning systems are capable of complex motor control tasks such as locomotion and manipulation, however, much of their underlying mech…
Tell Me Where to Go: A Composable Framework for Context-Aware Embodied Robot Navigation
Harel Biggie, Ajay Narasimha Mopidevi, Dusty Woods +1
Humans have the remarkable ability to navigate through unfamiliar environments by solely relying on our prior knowledge and descriptions of the environment. For robots to perform t…
Kalman Filter Auto-tuning through Enforcing Chi-Squared Normalized Error Distributions with Bayesian Optimization
Zhaozhong Chen, Harel Biggie, Nisar Ahmed +2
The nonlinear and stochastic relationship between noise covariance parameter values and state estimator performance makes optimal filter tuning a very challenging problem. Popular…
Looking Around Corners: Generative Methods in Terrain Extension
Alec Reed, Christoffer Heckman
In this paper, we provide an early look at our model for generating terrain that is occluded in the initial lidar scan or out of range of the sensor. As a proof of concept, we show…
Towards Decentralized Heterogeneous Multi-Robot SLAM and Target Tracking
Ofer Dagan, Tycho L. Cinquini, Luke Morrissey +3
In many robotics problems, there is a significant gain in collaborative information sharing between multiple robots, for exploration, search and rescue, tracking multiple targets,…
A New Wave in Robotics: Survey on Recent mmWave Radar Applications in Robotics
Kyle Harlow, Hyesu Jang, Timothy D. Barfoot +2
We survey the current state of millimeterwave (mmWave) radar applications in robotics with a focus on unique capabilities, and discuss future opportunities based on the state of th…
BO-ICP: Initialization of Iterative Closest Point Based on Bayesian Optimization
Harel Biggie, Andrew Beathard, Christoffer Heckman
Typical algorithms for point cloud registration such as Iterative Closest Point (ICP) require a favorable initial transform estimate between two point clouds in order to perform a…
Flexible Supervised Autonomy for Exploration in Subterranean Environments
Harel Biggie, Eugene R. Rush, Danny G. Riley +9
While the capabilities of autonomous systems have been steadily improving in recent years, these systems still struggle to rapidly explore previously unknown environments without t…
Present and Future of SLAM in Extreme Underground Environments
Kamak Ebadi, Lukas Bernreiter, Harel Biggie +28
This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT co…
Multi-Agent Autonomy: Advancements and Challenges in Subterranean Exploration
Michael T. Ohradzansky, Eugene R. Rush, Danny G. Riley +9
Artificial intelligence has undergone immense growth and maturation in recent years, though autonomous systems have traditionally struggled when fielded in diverse and previously u…
ColoRadar: The Direct 3D Millimeter Wave Radar Dataset
Andrew Kramer, Kyle Harlow, Christopher Williams +1
Millimeter wave radar is becoming increasingly popular as a sensing modality for robotic mapping and state estimation. However, there are very few publicly available datasets that…
Cooperative Control of Mobile Robots with Stackelberg Learning
Joewie J. Koh, Guohui Ding, Christoffer Heckman +2
Multi-robot cooperation requires agents to make decisions that are consistent with the shared goal without disregarding action-specific preferences that might arise from asymmetry…
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…
Formalizing and Guaranteeing* Human-Robot Interaction
Hadas Kress-Gazit, Kerstin Eder, Guy Hoffman +12
Robot capabilities are maturing across domains, from self-driving cars, to bipeds and drones. As a result, robots will soon no longer be confined to safety-controlled industrial se…
Distributed Reinforcement Learning for Cooperative Multi-Robot Object Manipulation
Guohui Ding, Joewie J. Koh, Kelly Merckaert +5
We consider solving a cooperative multi-robot object manipulation task using reinforcement learning (RL). We propose two distributed multi-agent RL approaches: distributed approxim…
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…
Extrinisic Calibration of a Camera-Arm System Through Rotation Identification
Steve McGuire, Christoffer Heckman, Daniel Szafir +2
Determining extrinsic calibration parameters is a necessity in any robotic system composed of actuators and cameras. Once a system is outside the lab environment, parameters must b…
Path-Following through Control Funnel Functions
Hadi Ravanbakhsh, Sina Aghli, Christoffer Heckman +1
We present an approach to path following using so-called control funnel functions. Synthesizing controllers to "robustly" follow a reference trajectory is a fundamental problem for…
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…