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View article: An Addendum to NeBula: Toward Extending Team CoSTAR’s Solution to Larger Scale Environments
An Addendum to NeBula: Toward Extending Team CoSTAR’s Solution to Larger Scale Environments Open
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, cr…
View article: Self-Supervised Traversability Prediction by Learning to Reconstruct Safe Terrain
Self-Supervised Traversability Prediction by Learning to Reconstruct Safe Terrain Open
Navigating off-road with a fast autonomous vehicle depends on a robust perception system that differentiates traversable from non-traversable terrain. Typically, this depends on a semantic understanding which is based on supervised learnin…
View article: Self-Supervised Traversability Prediction by Learning to Reconstruct Safe Terrain
Self-Supervised Traversability Prediction by Learning to Reconstruct Safe Terrain Open
Navigating off-road with a fast autonomous vehicle depends on a robust perception system that differentiates traversable from non-traversable terrain. Typically, this depends on a semantic understanding which is based on supervised learnin…
View article: Early Recall, Late Precision: Multi-Robot Semantic Object Mapping under Operational Constraints in Perceptually-Degraded Environments
Early Recall, Late Precision: Multi-Robot Semantic Object Mapping under Operational Constraints in Perceptually-Degraded Environments Open
Semantic object mapping in uncertain, perceptually degraded environments during long-range multi-robot autonomous exploration tasks such as search-and-rescue is important and challenging. During such missions, high recall is desirable to a…
View article: Simulation-Aided Handover Prediction From Video Using Recurrent Image-to-Motion Networks
Simulation-Aided Handover Prediction From Video Using Recurrent Image-to-Motion Networks Open
Recent advances in deep neural networks have opened up new possibilities for visuomotor robot learning. In the context of human-robot or robot-robot collaboration, such networks can be trained to predict future poses and this information c…
View article: Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching
Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching Open
sponsorship: This letter was recommended for publication by Associate Editor S. Behnke and Editor S. Bernard Williams upon evaluation of the reviewers' comments. This work was supported in part by the Jet Propulsion Laboratory, California …
View article: Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching
Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching Open
We consider the problem of rover relocalization in the context of the notional Mars Sample Return campaign. In this campaign, a rover (R1) needs to be capable of autonomously navigating and localizing itself within an area of approximately…
View article: Machine Vision based Sample-Tube Localization for Mars Sample Return
Machine Vision based Sample-Tube Localization for Mars Sample Return Open
A potential Mars Sample Return (MSR) architecture is being jointly studied by NASA and ESA. As currently envisioned, the MSR campaign consists of a series of 3 missions: sample cache, fetch and return to Earth. In this paper, we focus on t…
View article: Rover Relocalization for Mars Sample Return by Virtual Template\n Synthesis and Matching
Rover Relocalization for Mars Sample Return by Virtual Template\n Synthesis and Matching Open
We consider the problem of rover relocalization in the context of the\nnotional Mars Sample Return campaign. In this campaign, a rover (R1) needs to\nbe capable of autonomously navigating and localizing itself within an area of\napproximat…
View article: Smart hardware integration with advanced robot programming technologies for efficient reconfiguration of robot workcells
Smart hardware integration with advanced robot programming technologies for efficient reconfiguration of robot workcells Open
The manufacturing industry is seeing an increase in demand for more custom-made, low-volume production. This type of production is rarely automated and is to a large extent still performed manually. To keep up with the competition and mark…
View article: Training of deep neural networks for the generation of dynamic movement primitives
Training of deep neural networks for the generation of dynamic movement primitives Open
Dynamic movement primitives (DMPs) have proven to be an effective movement representation for motor skill learning. In this paper, we propose a new approach for training deep neural networks to synthesize dynamic movement primitives. The d…
View article: Cut & recombine: reuse of robot action components based on simple language instructions
Cut & recombine: reuse of robot action components based on simple language instructions Open
Human beings can generalize from one action to similar ones. Robots cannot do this and progress concerning information transfer between robotic actions is slow. We have designed a system that performs action generalization for manipulation…
View article: A System for Continuous Learning of Visual Concepts
A System for Continuous Learning of Visual Concepts Open
We present an artificial cognitive system for learning visual concepts. It comprises of vision, communication and manipulation subsystems, which provide visual input, enable verbal and non-verbal communication with a tutor and allow intera…
View article: Computational models of affordance in robotics: a taxonomy and systematic classification
Computational models of affordance in robotics: a taxonomy and systematic classification Open
J. J. Gibson’s concept of affordance, one of the central pillars of ecological psychology, is a truly remarkable idea that provides a concise theory of animal perception predicated on environmental interaction. It is thus not surprising th…
View article: Self-Supervised Online Learning of Basic Object Push Affordances
Self-Supervised Online Learning of Basic Object Push Affordances Open
Continuous learning of object affordances in a cognitive robot is a challenging problem, the solution to which arguably requires a developmental approach. In this paper, we describe scenarios where robotic systems interact with household o…