Calibrating a Multi-arm Multi-sensor Robot: A Bundle Adjustment Approach

Pradeep, Vijay; Konolige, Kurt; Berger, Eric

doi:10.1007/978-3-642-28572-1_15

Cited by 66 publications

(58 citation statements)

References 12 publications

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“…Extensions have been proposed to simultaneously calibrate robot and sensor (e.g., camera) parameters [24], [41]. These methods cannot account for errors resulting from material non-linearities such as cable stretch, prevalent in cost-effective cable-driven actuation mechanisms.…”

Section: Related Workmentioning

confidence: 99%

Autonomous multilateral debridement with the Raven surgical robot

Kehoe

Kahn

Mahler

et al. 2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

109

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Abstract-Robotic surgical assistants (RSAs) enable surgeons to perform delicate and precise minimally invasive surgery. Currently these devices are primarily controlled by surgeons in a local tele-operation (master-slave) mode. Introducing autonomy of surgical sub-tasks has the potential to assist surgeons, reduce fatigue, and facilitate supervised autonomy for remote tele-surgery. This paper considers the sub-task of surgical debridement: removing dead or damaged tissue fragments to allow the remaining healthy tissue to heal. We present an implemented automated surgical debridement system that uses the Raven, an open-architecture surgical robot with two cabledriven 7 DOF arms. Our system combines stereo vision for 3D perception, trajopt, an optimization-based motion planner, and model predictive control (MPC). Experiments with autonomous sensing, grasping, and removal of over 100 fragments suggest that it is possible for an autonomous surgical robot to achieve robustness comparable to human levels for a surgically-relevant subtask, although for our current implementation, execution time is 2-3× slower than human levels, primarily due to replanning times for MPC. This paper provides three contributions: (i) introducing debridement as a surgically-relevant sub-task for robotics, (ii) designing and implementing an autonomous multilateral surgical debridement system that uses both arms of the Raven surgical robot, and (iii) providing experimental data that highlights the importance of accurate state estimation for future research.

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Section: Related Workmentioning

confidence: 99%

Autonomous multilateral debridement with the Raven surgical robot

Kehoe

Kahn

Mahler

et al. 2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

109

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“…Pradeep et al [114] proposed an extendable framework that combined measurements from the robot's various sensors (proprioceptive and external) to calibrate the robot's joint offsets and external sensor locations. The framework was validated by implementing it on a commercial mobile manipulator robot, providing a significant improvement in the robot's calibration.…”

Section: Calibrationmentioning

confidence: 99%

Survey of Research for Performance Measurement of Mobile Manipulators

Bostelman¹,

Hong²,

Marvel³

2016

J. RES. NATL. INST. STAN.

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This survey provides the basis for developing research in the area of mobile manipulator performance measurement, an area that has relatively few research articles when compared to other mobile manipulator research areas. The survey provides a literature review of mobile manipulator research with examples of experimental applications. The survey also provides an extensive list of planning and control references as this has been the major research focus for mobile manipulators which factors into performance measurement of the system. The survey then reviews performance metrics considered for mobile robots, robot arms, and mobile manipulators and the systems that measure their performance, including machine tool measurement systems through dynamic motion tracking systems. Lastly, the survey includes a section on research that has occurred for performance measurement of robots, mobile robots, and mobile manipulators beginning with calibration, standards, and mobile manipulator artifacts that are being considered for evaluation of mobile manipulator performance.

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“…Suppose feature point f i has been matched. Then its measured coordinates on the normalized image plane, following (10), is given by…”

Section: Measurement Modelmentioning

confidence: 99%

“…In contrast to the earlier works, the proposed method in this paper is not restricted to horizontal planar features, but rather it is generalized for arbitrary planar features. This opens up for new applications where the plane under navigation is not horizontal but rather tilted or vertically aligned, e.g., in robotics [10].…”

Section: Introductionmentioning

confidence: 99%

Planar-based visual inertial navigation

Panahandeh

Händel

2015

2015 International Conference on Location and GNSS (ICL-GNSS)

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Abstract-This paper investigates the problem of visual-inertial navigation. The proposed navigation system integrates inertial information from an inertial measurement unit (IMU) with visual data from a camera to provide relative pose estimation for a system which is navigating in an unknown structural environment. The main contribution of this paper is derivation of a novel measurement model based on inertial data and visual planar features. The proposed formulation is a solution to the 6-DoF motion estimation where the IMU-camera movement is not restricted over a desired navigation plane. Compared to previous works, which are restricted on using only horizontal plane features, the proposed model is generalized for arbitrary planar features. The theoretical finding of this study is extensively evaluated both with simulation and real world experiments. The presented experiments indicate the reliability of the proposed method to perform accurate 6-DoF pose estimation.

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Calibrating a Multi-arm Multi-sensor Robot: A Bundle Adjustment Approach

Cited by 66 publications

References 12 publications

Autonomous multilateral debridement with the Raven surgical robot

Autonomous multilateral debridement with the Raven surgical robot

Survey of Research for Performance Measurement of Mobile Manipulators

Planar-based visual inertial navigation

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