Exploiting visual constraints in the synthesis of uncertainty-tolerant motion plans

Fox, A.; Hutchinson, Seth

doi:10.1109/70.345938

Cited by 23 publications

(5 citation statements)

References 35 publications

(13 reference statements)

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“…In particular, the design of motion strategies that plan an occlusion-free path offline or online are of interest. Offline vision planning using visibility models and a prior world model information has already been investigated [34], [35]. Online motion compensation based on occlusion detection does not appear to have been considered to date.…”

Section: Discussionmentioning

confidence: 99%

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A modular system for robust positioning using feedback from stereo vision

Hager

1997

IEEE Trans. Robot. Automat.

144

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Abstract-This paper introduces a modular framework for robot motion control using stereo vision. The approach is based on a small number of generic motion control operations referred to as primitive skills. Each primitive skill uses visual feedback to enforce a specific task-space kinematic constraint between a robot end-effector and a set of target features. By observing both the end-effector and target features, primitive skills are able to position with an accuracy that is independent of errors in handeye calibration. Furthermore, primitive skills are easily combined to form more complex kinematic constraints as required by different applications. These control laws have been integrated into a system that performs tracking and control on a single processor at real-time rates. Experiments with this system have shown that it is extremely accurate, and that it is insensitive to camera calibration error. The system has been applied to a number of example problems, showing that modular, high precision, vision-based motion control is easily achieved with off-the-shelf hardware.

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Section: Discussionmentioning

confidence: 99%

“…Let be the error term with the corresponding elements deleted. Then the Jacobian relating the end-effector screw to stereo point motion is (35) and the end-effector screw is given by (…”

Section: A Three Positioning Primitives 1) Point-to-point Positioningmentioning

confidence: 99%

A modular system for robust positioning using feedback from stereo vision

Hager

1997

IEEE Trans. Robot. Automat.

144

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“…Fine motion planning using visual constraints [59] that have been modified by diffraction effects at the micro-scale is also an area of research. Finally, how these goal regions affect planning under uncertainty needs to be addressed.…”

Section: Discussionmentioning

confidence: 99%

Ultra-Precise Assembly of Micro-Electromechanical Systems (MEMS) Components

Feddema¹,

Simon²,

Polosky³

et al. 1999

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“…That motivation is rooted in a long line of work on motion planning with uncertainty from the 1980s and 1990s [9,59,60,22,10,14,12,72,15,16,53,33,55,11] as well as related work on understanding information invariants, such as natural tradeoffs between sensing and action [70,21,18,2,19,52,26,17,45,46]. The tools for characterizing system capabilities discussed in Sections 9 and 10 provide a concise topological language for making such comparisons.…”

Section: An Underlying Motivationmentioning

confidence: 99%

On the Topology of Discrete Strategies

Erdmann

2009

The International Journal of Robotics Research

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This paper explores a topological perspective of planning in the presence of uncertainty, focusing on tasks specified by goal states in discrete spaces. The paper introduces strategy complexes. A strategy complex is the collection of all plans for attaining all goals in a given space. Plans are like jigsaw pieces. Understanding how the pieces fit together in a strategy complex reveals structure. That structure characterizes the inherent capabilities of an uncertain system. By adjusting the jigsaw pieces in a design loop, one can build systems with desired competencies.The paper draws on representations from combinatorial topology, Markov chains, and polyhedral cones. Triangulating between these three perspectives produces a topological language for describing concisely the capabilities of uncertain systems, analogous to concepts of reachability and controllability in other disciplines. The major nouns in this language are topological spaces.Three key theorems (numbered 1, 11, 20 in the paper) illustrate the sentences in this language: (a) Goal Attainability: There exists a strategy for attaining a particular goal from anywhere in a system if and only if the strategy complex of a slightly modified system is homotopic to a sphere. (b) Full Controllability: A system can move between any two states despite control uncertainty precisely when its strategy complex is homotopic to a sphere of dimension two less than the number of states. (c) General Structure: Any system's strategy complex is homotopic to the product of a spherical part, modeling full controllability on subspaces, and a general part, modeling adversarial capabilities.The paper contains a number of additional results required as stepping stones, along with many examples. The paper provides algorithms for computing the key structures described. Finally, the paper shows that some interesting questions are hard. For instance, it is NP -complete to determine the most precisely attainable goal of a system with perfect sensing but uncertain control.

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Exploiting visual constraints in the synthesis of uncertainty-tolerant motion plans

Cited by 23 publications

References 35 publications

A modular system for robust positioning using feedback from stereo vision

A modular system for robust positioning using feedback from stereo vision

Ultra-Precise Assembly of Micro-Electromechanical Systems (MEMS) Components

On the Topology of Discrete Strategies

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