Name
Abstract | ||
|---|---|---|
Force and vision sensors provide complementary information, yet they are fundamentally different sensing modalities. This implies that traditional sensor integration techniques that require common data representations are not appropriate for combining the feedback from these two disparate sensors. In this paper, we introduce the concept of vision and force sensor resolvability as a means of comparing the ability of the two sensing modes to provide useful information during robotic manipulation tasks. By monitoring the resolvability of the two sensing modes with respect to the task, the information provided by the disparate sensors can be seamlessly assimilated during task execution. A nonlinear force/vision servoing algorithm that uses force and vision resolvability to switch manipulator control between sensors is proposed. The advantages of the assimilation technique are demonstrated during contact transitions between a stiff manipulator and a rigid environment, a system configuration that easily becomes unstable when force control alone is used. Experimental results show that robust contact transitions are made by the proposed nonlinear controller while simultaneously satisfying the conflicting task requirements of fast approach velocities, maintaining stability, minimizing impact forces, and suppressing bounce between contact surfaces |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1109/70.538976 | Robotics and Automation, IEEE Transactions |
Keywords | Field | DocType |
feedback,force control,force measurement,image sensors,intelligent control,manipulators,nonlinear control systems,servomechanisms,bounce suppression,common data representations,contact transitions,disparate sensory feedback assimilation,fast approach velocities,force sensor,impact force minimization,manipulator control,nonlinear force/vision servoing algorithm,resolvability,rigid environment,robotic manipulation tasks,sensor integration techniques,sensor resolvability,stability,stiff manipulator,vision sensors,rigidity,velocity,visual servoing,control,algorithms,control systems,visual perception,surfaces,satisfiability,switches,impact strength,data representation,human factors engineering,vision,indexing terms,computer vision,detectors,requirements,assimilation,nonlinear systems | Control theory,Control engineering,Servomechanism,Artificial intelligence,Control system,Robotics,Visual perception,Intelligent control,Computer vision,Control theory,Image sensor,Visual control,Mathematics | Journal |
Volume | Issue | ISSN |
12 | 5 | 1042-296X |
Citations | PageRank | References |
42 | 3.74 | 35 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bradley J. Nelson | 1 | 1263 | 202.74 |
| Khosla, P.K. | 2 | 931 | 123.84 |