activity
20182022
most citedEdge SLAM: Edge Points Based Monocular Visual SLAM

52 citations · 78 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.RO20221 cited

Object Goal Navigation Based on Semantics and RGB Ego View

Snehasis Banerjee, Brojeshwar Bhowmick, Ruddra Dev Roychoudhury

This paper presents an architecture and methodology to empower a service robot to navigate an indoor environment with semantic decision making, given RGB ego view. This method leve…

cs.RO2021

Sharing Cognition: Human Gesture and Natural Language Grounding Based Planning and Navigation for Indoor Robots

Gourav Kumar, Soumyadip Maity, Ruddra dev Roychoudhury +1

Cooperation among humans makes it easy to execute tasks and navigate seamlessly even in unknown scenarios. With our individual knowledge and collective cognition skills, we can rea…

cs.RO2021

DeepMPCVS: Deep Model Predictive Control for Visual Servoing

Pushkal Katara, Y V S Harish, Harit Pandya +5

The simplicity of the visual servoing approach makes it an attractive option for tasks dealing with vision-based control of robots in many real-world applications. However, attaini…

cs.RO20193 cited

Integrating Objects into Monocular SLAM: Line Based Category Specific Models

Nayan Joshi, Yogesh Sharma, Parv Parkhiya +3

We propose a novel Line based parameterization for category specific CAD models. The proposed parameterization associates 3D category-specific CAD model and object under considerat…

cs.RO2019

Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences

Vignesh Prasad, Dipanjan Das, Brojeshwar Bhowmick

Deep approaches to predict monocular depth and ego-motion have grown in recent years due to their ability to produce dense depth from monocular images. The main idea behind them is…

cs.RO2018

SfMLearner++: Learning Monocular Depth & Ego-Motion using Meaningful Geometric Constraints

Vignesh Prasad, Brojeshwar Bhowmick

Most geometric approaches to monocular Visual Odometry (VO) provide robust pose estimates, but sparse or semi-dense depth estimates. Off late, deep methods have shown good performa…