Drone Landing

Uncertainty Constrained Differential Dynamic Programming in Belief Space for Vision Based Robots

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Shatil Rahman, and Steven L. Waslander. 

IEEE Robotics and Automation Letters (RA-L), 2021

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A novel trajectory optimization formulation that incorporates inequality constraints on uncertainty and a novel Augmented Lagrangian based stochastic differential dynamic programming method in belief space.

DC-VINS: Dynamic Camera Visual Inertial Navigation System with Online Calibration

Jason Rebello, Chunshang Li and Steven L. Waslander.
ICCV Workshop, 2021

we present the online extrinsic calibration between a dynamic camera mounted to an actuated mechanism and an IMU mounted to the body of the vehicle integrated into a Visual Odometry pipeline.

Towards End-to-end Learning of Visual Inertial Odometry with an EKF

Chunshang Li and S.L. Waslander
Conference on Computer and Robot Vision (CRV), 2020

In this paper, we propose the first end-to-end trainable visual-inertial odometry (VIO) algorithm that leverages a robo-centric Extended Kalman Filter (EKF)..

AC/DCC: Accurate Calibration of Dynamic Camera Clusters for Visual SLAM

Jason Rebello, Augus Fung and Steven L. Waslander
International Conference on Robotics and Automation (ICRA),, 2020

A novel method that performs accurate calibration of a Dynamic Camera Cluster with multiple static cameras using a pose-loop error formulation. We also present an analysis of the degenerate parameters.

Visual Measurement Integrity Monitoring for UAV Localization

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Chengyao Li, and Steven L. Waslander. 

IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2019

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A novel approach inspired by RAIM to monitor the integrity of visual localization for UAV. The algorithm first detects and rejects measurement outliers and calculates the protection level of the position estimation.

Towards Robust Autonomous MAV Landing with a Gimbal Camera

Christopher Choi and Steven L. Waslander.
2018

A more robust autonomous landing system for MAVs using a gimbal camera with complete tracking and landing modules. Results are present for both simulation and real MAVs.

Encoderless Gimbal Calibration of Dynamic Multi-Camera Clusters

Christopher L. Choi, Jason Rebello, Leonid Koppel, Pranav Ganti, Arun Das, and Steven L. Waslander
International Conference on Robotics and Automation (ICRA), 2018

Calibration of a DCC was performed without knowledge of joint encoder angles and tested in a Visual Intertial Odometry application.​

Autonomous Active Calibration of a Dynamic Camera Cluster using Next-Best-View

Jason Rebello, Arun Das and Steven L. Waslander
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017

A novel active vision approach to DCC calibration, which directly reduces parameter uncertainty by selecting calibration measurements using an information theoretic next-best-view policy was developed.

Calibration of a Dynamic Camera Cluster for Multi-Camera Visual SLAM

Arun Das and Steven L. Waslander
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016

A calibration method for dynamic multi-camera clusters, where one or more of the cameras is mounted to an actuated mechanism such as a gimbal or robotic manipulator.

Autonomous Maritime Landings for Low-cost VTOL Aerial Vehicles

Kevin Ling, Derek Chow, Arun Das, and Steven L. Waslander
Conference on Computer and Robot Vision (CRV), 2014

An autonomous landing system of UAV on a maritime vessel using an architecture that avoids sensor limitations while allowing for accurate relative pose estimation, even in the presence of wind disturbances.