Composition of local potential functions for global robot control and navigation

Conner, David C.; Rizzi, Alfred A.; Choset, Howie

doi:10.1109/iros.2003.1249705

Cited by 113 publications

(115 citation statements)

References 11 publications

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“…Mason [18] first introduced the concept in the context of performing sensorless manipulation actions that employ passive mechanics to reduce part uncertainty. Later, Burridge et al [3] applied the funnel analogy to feedback control in the form of sequential composition of controllers, spawning much follow-on work [7,8,24]. This body of work is sensor-agnostic in that the type and quality of sensor data is assumed to be homogeneous throughout the configuration space.…”

Section: Sequential Composition Of Sensorsmentioning

confidence: 99%

Towards Coordinated Precision Assembly with Robot Teams

Dogar¹,

Knepper²,

Spielberg³

et al. 2015

Experimental Robotics

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Abstract. We present a system in which a flexible team of robots coordinate to assemble large, complex, and diverse structures autonomously. Our system operates across a wide range of spatial scales and tolerances, using a hierarchical perception architecture. For the successful execution of very precise assembly operations under initial uncertainty, our system starts with high-field of view but low accuracy sensors, and gradually use low field-of-view but high accuracy sensors. Our system also uses a failure detection and recovery system, integrated with this hierarchical perception architecture: upon losing track of a feature, our system retracts to using high-field of view systems to re-localize. Additionally, we contribute manipulation skills and tools necessary to assemble large structures with high precision. First, the team of robots coordinate to transport large assembly parts which are too heavy for a single robot to carry. Second, we develop a new tool which is capable of co-localizing holes and fasteners for robust insertion and fastening. We present real robot experiments where we measure the contribution of the hierarchical perception and failure recovery approach to the robustness of our system. We also present an extensive set of experiments where our robots successfully insert all 80 of the attempted fastener insertion operations.

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Section: Sequential Composition Of Sensorsmentioning

confidence: 99%

Towards Coordinated Precision Assembly with Robot Teams

Dogar¹,

Knepper²,

Spielberg³

et al. 2015

Experimental Robotics

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show abstract

“…Fully-actuated first-order visual servo control is largely a solved problem [1] and, in particular, smooth stabilizability opens the door to the full suite of navigation function (NF) methods [7], including the lift to second-order dynamics [17] that can preserve all the first-order guarantees-not merely convergence, but obstacle avoidance [18], and robustness against disturbances as well [19]. Recent work incorporating visual servo methods into global landmark-based localization, navigation and mapping [20], [21] suggests the powerful role that effectively stabilized visual servo loops can achieve in complex task settings.…”

Section: A Related Literaturementioning

confidence: 99%

Active sensing for dynamic, non-holonomic, robust visual servoing

Bayer

Koditschek

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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We consider the problem of visually servoing a legged vehicle with unicycle-like nonholonomic constraints subject to second-order fore-aft dynamics in its horizontal plane. We target applications to rugged environments characterized by complex terrain likely to perturb significantly the robot's nominal dynamics. At the same time, it is crucial that the camera avoid "obstacle" poses where absolute localization would be compromised by even partial loss of landmark visibility. Hence, we seek a controller whose robustness against disturbances and obstacle avoidance capabilities can be assured by a strict global Lyapunov function. Since the nonholonomic constraints preclude smooth point stabilizability we introduce an extra degree of sensory freedom, affixing the camera to an actuated panning axis mounted on the robot's back. Smooth stabilizability to the robot-orientation-indifferent goal cycle no longer precluded, we construct a controller and strict global Lyapunov function with the desired properties. We implement several versions of the scheme on a RHex robot maneuvering over slippery ground and document its successful empirical performance. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/ese_papers/661Active Sensing for Dynamic, Non-holonomic, Robust Visual Servoing Avik De , Karl S. Bayer † and Daniel E. Koditschek Abstract-We consider the problem of visually servoing a legged vehicle with unicycle-like nonholonomic constraints subject to second-order fore-aft dynamics in its horizontal-plane. We target applications to rugged environments characterized by complex terrain likely to significantly perturb the robot's nominal dynamics. At the same time, it is crucial that the camera avoid "obstacle" poses where absolute localization would be compromised by even partial loss of landmark visibility. Hence, we seek a controller whose robustness against disturbances and obstacle avoidance capabilities can be assured by a strict global Lyapunov function. Since the nonholonomic constraints preclude smooth point stabilizability we introduce an extra degree of sensory freedom, affixing the camera to an actuated panning axis on the robot's back. Smooth stabilizability to the robot-orientation-indifferent goal cycle no longer precluded, we construct a controller and strict global Lyapunov function with the desired properties. We implement several versions of the scheme on a RHex robot maneuvering over slippery...

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“…In order to overcome these problems, feedback motion planning approaches take into account feedback concerns during collision-free path computation. Rather than planning a single collision-free path between the initial and goal configurations, these approaches compute a feedback plan over the entire free space of the robot that can converge towards the goal [4], [5]. A feedback plan is often represented as a vector field over the free space.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the prior work on computing global vector fields for feedback motion planning is based on sequential composition [4], [5], [6], [7]. In these approaches, the robot's free space is decomposed into cells.…”

Section: Introductionmentioning

confidence: 99%

Global vector field computation for feedback motion planning

Zhang

LaValle

Manocha

2009

2009 IEEE International Conference on Robotics and Automation

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Abstract-We present a global vector field computation algorithm in configuration spaces for smooth feedback motion planning. Our algorithm performs approximate cell decomposition in the configuration space and approximates the free space using rectanguloid cells. We compute a smooth local vector field for each cell in the free space and address the issue of the smooth composition of the local vector fields between the non-uniform adjacent cells. We show that the integral curve over the computed vector field is guaranteed to converge to the goal configuration, be collision-free, and maintain C ∞ smoothness. As compared to prior approaches, our algorithm works well on non-convex robots and obstacles. We demonstrate its performance on planar robots with 2 or 3 DOFs, articulated robots composed of 3 serial links and multi-robot systems with 6 DOFs.

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Composition of local potential functions for global robot control and navigation

Cited by 113 publications

References 11 publications

Towards Coordinated Precision Assembly with Robot Teams

Towards Coordinated Precision Assembly with Robot Teams

Active sensing for dynamic, non-holonomic, robust visual servoing

Global vector field computation for feedback motion planning

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