Adaptive object centered teleoperation control of a mobile manipulator

Båberg, Fredrik; Wang, Yuquan; Caccamo, Sergio; Ögren, Petter

doi:10.1109/icra.2016.7487166

Cited by 4 publications

(5 citation statements)

References 20 publications

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“…Given the limitations of low-dimensional devices, their control coordinate systems should be carefully selected as the control coordinate systems represent which subspace the robot can move in. While many existing systems attach the control coordinate system to the ground plane [5], [11], [25] or the camera image plane [5], [8], [24], several alternative choices may be appropriate. In this paper, by articulating a design space of control coordinate systems, we introduce a hybrid frame that is specifically designed for low-dimensional input devices.…”

Section: Telemanipulation With Low-dimensional Input Devicesmentioning

confidence: 99%

“…Some of the control coordinate systemare attached to some imaginary objects. For example, several works [5], [25], [34] drew inspiration from orbit camera control methods in computer graphics. Orbit control moves the end-effector along the surface of an imaginary sphere, creating orbital motions (Figure 2A).…”

Section: Organizing Existing Control Coordinate Systemsmentioning

confidence: 99%

“…End-effector frame [5], [9]- [11] End-effector x-axis End-effector y-axis Orbit control -Fig. 2A [5], [25] End-effector right (in a spherical coordinate system) End-effector up (in a spherical coordinate system) Spray task frame -Fig. 2C humans inherently maintain a stable perception of the vertical direction despite changing viewpoints, which is known as orientation constancy [45].…”

Section: Design Criteriamentioning

confidence: 99%

“…Control coordinate systems A and B are designed for 3D input devices; C and D are for 2D input devices. A. Orbit control [5], [25], [34] -The control coordinate system moves on an imaginary sphere, whose radius is controlled by the blue axis. B. Pour task frame [36] -Vertical inputs move the bottle vertically up and down (blue arrow).…”

Section: E Summarymentioning

confidence: 99%

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A Design Space of Control Coordinate Systems in Telemanipulation

Wang,

Praveena,

Gleicher

2024

IEEE Access

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Teleoperation systems map operator commands from an input device into some coordinate frame in the remote environment. This frame, which we call a control coordinate system, should be carefully chosen as it determines how operators should move to get desired robot motions. While specific choices made by individual systems have been described in prior work, a design space, i.e., an abstraction that encapsulates the range of possible options, has not been codified. In this paper, we articulate a design space of control coordinate systems, which can be defined by choosing a direction in the remote environment for each axis of the input device. Our key insight is that there is a small set of meaningful directions in the remote environment. Control coordinate systems in prior works can be organized by the alignments of their axes with these directions and new control coordinate systems can be designed by choosing from these directions. We also provide three design criteria to reason about the suitability of control coordinate systems for various scenarios. To demonstrate the utility of our design space, we use it to organize prior systems and design control coordinate systems for three scenarios that we assess through human-subject experiments. Our results highlight the promise of our design space as a conceptual tool to assist system designers to design control coordinate systems that are effective and intuitive for operators.

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Section: Telemanipulation With Low-dimensional Input Devicesmentioning

confidence: 99%

Section: Organizing Existing Control Coordinate Systemsmentioning

confidence: 99%

Section: Design Criteriamentioning

confidence: 99%

Section: E Summarymentioning

confidence: 99%

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A Design Space of Control Coordinate Systems in Telemanipulation

Wang,

Praveena,

Gleicher

2024

IEEE Access

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“…Many authors use it to simulate aircraft design and testing steps [24]. Others use it to simulate industrial, underwater and other robot mechanisms [25,26].…”

Section: Introductionmentioning

confidence: 99%

Cognitive Model of the Closed Environment of a Mobile Robot Based on Measurements

Pavlic¹,

Kušec²,

Radočaj³

et al. 2021

Applied Sciences

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In recent years in mobile robotics, the focus has been on methods, in which the fusion of measurement data from various systems leads to models of the environment that are of a probabilistic type. The cognitive model of the environment is less accurate than the exact mathematical one, but it is unavoidable in the robot collaborative interaction with a human. The subject of the research proposed in this paper is the development of a model for learning and planning robot operations. The task of operations and mapping the unknown environment, similar to how humans do the same tasks in the same conditions has been explored. The learning process is based on a virtual dynamic model of a mobile robot, identical to a real mobile robot. The mobile robot’s motion with developed artificial neural networks and genetic algorithms is defined. The transfer method of obtained knowledge from simulated to a real system (Sim-To-Real; STR) is proposed. This method includes a training step, a simultaneous reasoning step, and an application step of trained and learned knowledge to control a real robot’s motion. Use of the basic cognitive elements language, a robot’s environment, and its correlation to that environment is described. Based on that description, a higher level of information about the mobile robot’s environment is obtained. The information is directly generated by the fusion of measurement data obtained from various systems.

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