Control allocation for mobile manipulators with on-board cameras

Pham, Cong Dung; From, Pål Johan

doi:10.1109/iros.2013.6697079

Cited by 10 publications

(4 citation statements)

References 15 publications

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“…In Yamamoto and Yun (1992) motion coordination is achieved by making a specific reference point on the mobile platform follow a trajectory calculated algebraically by the manipulability index of the 2-link non-redundant manipulator. Another approach for groundbased mobile robots are presented in Pham and From (2013), where a virtual mass-damper-spring system is inserted between the mobile base and the end-effector. Kinematic control of a UVMS using the task priority approach is presented in e.g.…”

Section: Fig 1 Underwater Swimming Manipulatormentioning

confidence: 99%

A control framework for biologically inspired underwater swimming manipulators equipped with thrusters**This research was partly funded by the Research Council of Norway through the Centres of Excellence funding scheme, project No. 223254 NTNU AMOS, and partly funded by VISTA, a basic research program in collaboration between The Norwegian Academy of Science and Letters, and Statoil.

et al. 2016

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In this paper we present a control framework for a novel biologically inspired underwater swimming manipulator (USM) equipped with thrusters. The framework consists of a kinematic part and a dynamic part. The kinematic part of the framework controls the velocity of the head link of the USM by coordinating the motion of the body of the USM and the articulated joints. Various methods based on inverse kinematics is presented and the applicability of each method for kinematic control of the USM is discussed. The dynamic part of the framework ensures that the velocity references generated by the inverse kinematics method are followed and that the thruster forces are appropriately distributed among the available thrusters. The significance of the relationship between the inverse kinematics routine and the thruster allocation algorithm is explained and simulations are included to validate the concept for control of the USM.

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Section: Fig 1 Underwater Swimming Manipulatormentioning

confidence: 99%

A control framework for biologically inspired underwater swimming manipulators equipped with thrusters**This research was partly funded by the Research Council of Norway through the Centres of Excellence funding scheme, project No. 223254 NTNU AMOS, and partly funded by VISTA, a basic research program in collaboration between The Norwegian Academy of Science and Letters, and Statoil.

et al. 2016

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“…In this section we describe the third control scheme, first presented in Pham and From (2013), which introduces artificial forces between the end-effector and the base.…”

Section: Strategy III -Control Allocationmentioning

confidence: 99%

Evaluation of Subjective and Objective Performance Metrics for Haptically Controlled Robotic Systems

Pham¹,

Phan²,

From

2014

MIC

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This paper studies in detail how different evaluation methods perform when it comes to describing the performance of haptically controlled mobile manipulators. Particularly, we investigate how well subjective metrics perform compared to objective metrics. To find the best metrics to describe the performance of a control scheme is challenging when human operators are involved; how the user perceives the performance of the controller does not necessarily correspond to the directly measurable metrics normally used in controller evaluation. It is therefore important to study whether there is any correspondence between how the user perceives the performance of a controller, and how it performs in terms of directly measurable metrics such as the time used to perform a task, number of errors, accuracy, and so on.To perform these tests we choose a system that consists of a mobile manipulator that is controlled by an operator through a haptic device. This is a good system for studying different performance metrics as the performance can be determined by subjective metrics based on feedback from the users, and also as objective and directly measurable metrics. The system consists of a robotic arm which provides for interaction and manipulation, which is mounted on a mobile base which extends the workspace of the arm. The operator thus needs to perform both interaction and locomotion using a single haptic device. While the position of the on-board camera is determined by the base motion, the principal control objective is the motion of the manipulator arm. This calls for intelligent control allocation between the base and the manipulator arm in order to obtain intuitive control of both the camera and the arm. We implement three different approaches to the control allocation problem, i.e., whether the vehicle or manipulator arm actuation is applied to generate the desired motion. The performance of the different control schemes is evaluated, and our findings strongly suggest that objective metrics better describe the performance of the controller, even though there is a clear correlation between subjective and objective performance metrics.

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“…This is the problem of how to interpret the master reference (6 DoF) as both position and velocity references and how to distribute the control forces between the vehicle and the base (3+6 DoF). We refer to Pham and From [2013] for more details on the implementation of the control laws…”

Section: Control Objectivementioning

confidence: 99%

Comparison of Mental and Theoretical Evaluations of Remotely Controlled Mobile Manipulators

Pham

Phan

From

2014

IFAC Proceedings Volumes

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Abstract:The focus of this research is to compare the mental and theoretical evaluations of remotely controlled mobile manipulators. Evaluating the performance of control methods for mobile manipulation is challenging because both the user experience and the actual performance of the completed task need to be taken into account. How the user perceives the control law is of course very subjective and in general hard do quantify numerically. Theoretical evaluations of the performance are easier to find, but do not tell us anything about the stress, frustration, and mental demand that the operator experiences. Several studies have been performed to evaluate the performance of teleoperation schemes, but the literature lacks a comparison between objective and subjective performance metrics for evaluating these. In this paper we evaluate the mental and theoretical performance of three relatively simple approaches for controlling a mobile manipulator with a haptic device. We study to what extent objective performance metrics such as execution time, number of failures, and manipulator mobility can be used to distinguish the approaches, and compare this to subjective measures like the NASA-TLX test.

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Control allocation for mobile manipulators with on-board cameras

Cited by 10 publications

References 15 publications

Evaluation of Subjective and Objective Performance Metrics for Haptically Controlled Robotic Systems

Comparison of Mental and Theoretical Evaluations of Remotely Controlled Mobile Manipulators

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