Camera-IMU-based localization: Observability analysis and consistency improvement

Hesch, Joel A.; Kottas, Dimitrios G.; Bowman, Sean L.; Roumeliotis, Stergios I.

doi:10.1177/0278364913509675

Cited by 206 publications

(138 citation statements)

References 33 publications

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“…For smoother and more accurate pose estimation, we fuse this LiDAR-SLAM pose information with the IMU data via extended Kalman filtering (EKF). For this, following (Hesch et al 2014;Lee et al 2016), we utilize the IMU data (only accelerometer in (x, y) and yaw gyroscope used) for the EKF propagation step (with 250 Hz), while the LiDAR-SLAM data for the EKF measurement update (with 40 Hz). We also adopt the technique of error-state EKF for faster and more robust estimation performance (Hesch et al 2014).…”

Section: Ekf Pose Estimation Of Leader Wmrmentioning

confidence: 99%

Teleoperation of a platoon of distributed wheeled mobile robots with predictive display

Yoon

Kim

et al. 2018

Auton Robot

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We propose a novel teleoperation framework for multiple distributed non-holonomic mobile robots (WMR), each equipped with onboard sensing and computing using peer-to-peer communication. One of the WMRs is designated as the leader with the first-person view camera and SLAM, while the other WMRs maintain a certain desired formation relative to their respective fore-running WMR in a distributed manner. For this, we first utilize nonholonomic passive decomposition to split the platoon kinematics into that of the formation-keeping aspect and the collective tele-driving aspect. We then design the controls for these two aspects individually and distribute them into each WMR while incorporating their nonholonomic constraint and distribution requirement. We also propose a novel predictive display, which, by providing the user with the estimated current and predicted future pose of the platoon and future possibility of collision while incorporating the uncertainty inherent to the distribution, can significantly enhance the tele-driving performance. Experiments and user study are also performed.

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Section: Ekf Pose Estimation Of Leader Wmrmentioning

confidence: 99%

Teleoperation of a platoon of distributed wheeled mobile robots with predictive display

Yoon

Kim

et al. 2018

Auton Robot

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“…Thus, the control inputs are dependent on s (2) , s (3) , s (4) ,ψ, andψ, and the dynamic system could be rewritten as a chain of integrators for each of the elements of Y with the appropriate derivative as the input to the flat system. For this reason, we plan trajectories that minimize the fourth derivative (i.e.…”

Section: B Image Features In a Fixed-orientation Virtual Framementioning

confidence: 99%

“…Estimation using stereo cameras has proven to be effective [2], but requires heavy processing capabilities and a pair of calibrated cameras, which increases the weight and cost of the vehicle while decreasing the agility. Recent work has shown the feasibility of using a single monocular camera and an IMU for real-time localization [4]- [6] and autonomous flight [3], [7]- [9]. In these papers, information from the two sensors is fused using an Extended Kalman Filter (EKF) or an Unscented Kalman Filter (UKF) in order to provide localization that is viable for real-time control.…”

Section: Introductionmentioning

confidence: 99%

Visual Servoing of Quadrotors for Perching by Hanging From Cylindrical Objects

Thomas

Loianno

Daniilidis

et al. 2016

IEEE Robot. Autom. Lett.

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This paper addresses vision-based localization and servoing for quadrotors to enable autonomous perching by hanging from cylindrical structures using only a monocular camera. We focus on the problems of relative pose estimation, control, and trajectory planning for maneuvering a robot relative to cylinders with unknown orientations. We first develop a geometric model that describes the pose of the robot relative to a cylinder. Then, we derive the dynamics of the system, expressed in terms of the image features. Based on the dynamics, we present a controller which guarantees asymptotic convergence to the desired image space coordinates. Finally, we develop an effective method to plan dynamically-feasible trajectories in the image space, and we provide experimental results to demonstrate the proposed method under different operating conditions such as hovering, trajectory tracking, and perching. Abstract-This paper addresses vision-based localization and servoing for quadrotors to enable autonomous perching by hanging from cylindrical structures using only a monocular camera. We focus on the problems of relative pose estimation, control, and trajectory planning for maneuvering a robot relative to cylinders with unknown orientations. We first develop a geometric model that describes the pose of the robot relative to a cylinder. Then, we derive the dynamics of the system, expressed in terms of the image features. Based on the dynamics, we present a controller which guarantees asymptotic convergence to the desired image space coordinates. Finally, we develop an effective method to plan dynamically-feasible trajectories in the image space, and we provide experimental results to demonstrate the proposed method under different operating conditions such as hovering, trajectory tracking, and perching.

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“…The presented VINS observability analyses in [8][9][10]16,19,38] are among the most recent related works, which specifically study observability properties of the INS state variables for motion estimation in unknown environments. For instance, the analyses in [8,16] result in four unobservable directions, corresponding to global translations and global rotation about the gravity vector.…”

Section: Vins Observability Analysismentioning

confidence: 99%

“…This can be challenging especially for high-dimensional systems, such as the VINS. To address this issue, in the following section we present the method of [5,9] for proving that a system is unobservable and finding its unobservable directions.…”

Section: Observability Analysis With Lie Derivativesmentioning

confidence: 99%

Planar-Based Visual Inertial Navigation: Observability Analysis and Motion Estimation

Panahandeh

Hutchinson

Händel

et al. 2015

J Intell Robot Syst

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In this paper, we address the problem of ego-motion estimation by fusing visual and inertial information. The hardware consists of an inertial measurement unit (IMU) and a monocular camera. The camera provides visual observations in the form of features on a horizontal plane. Exploiting the geometric constraint of features on the plane into visual and inertial data, we propose a novel closed form measurement model for this system. Our first contribution in this paper is an observability analysis of the proposed planar-based visual inertial navigation system (VINS). In particular, we prove that the system has only three unobservable states corresponding to global translations parallel to the plane, and rotation around the gravity vector. Hence, compared to general VINS, an advantage of using features on the horizontal plane is that the vertical translation along the normal of the plane becomes observable. As the second contribution, we present a state-space formulation for the pose estimation in the analyzed system and solve it via a modified unscented Kalman filter (UKF). Finally, the findings of the theoretical analysis and 6-DoF motion estimation are validated by simulations as well as using experimental data.

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Camera-IMU-based localization: Observability analysis and consistency improvement

Cited by 206 publications

References 33 publications

Teleoperation of a platoon of distributed wheeled mobile robots with predictive display

Teleoperation of a platoon of distributed wheeled mobile robots with predictive display

Visual Servoing of Quadrotors for Perching by Hanging From Cylindrical Objects

Planar-Based Visual Inertial Navigation: Observability Analysis and Motion Estimation

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