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AadilMehdi Sanchawala

3 accepted papers

2021

DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects

Rahul Sajnani, AadilMehdi Sanchawala, Krishna Murthy Jatavallabhula, Srinath Sridhar, K. Madhava Krishna
ICRA 2021poster

We present DRACO, a method for Dense Reconstruction And Canonicalization of Object shape from one or more RGB images. Canonical shape reconstruction— estimating 3D object shape in a coordinate space canonicalized for scale, rotation, and translation parameters—is an emerging paradigm that holds prom…

Cited by 6Source ↗code ↗Scholar ↗
2021

RTVS: A Lightweight Differentiable MPC Framework for Real-Time Visual Servoing

M. Nomaan Qureshi, Pushkal Katara, Abhinav Gupta, Harit Pandya, Y V S Harish, AadilMehdi Sanchawala +3
IROS 2021poster

Recent data-driven approaches to visual servoing have shown improved performances over classical methods due to precise feature matching and depth estimation. Some recent servoing approaches use a model predictive control (MPC) framework which generalise well to novel environments and are capable of…

Cited by 6Source ↗Scholar ↗
2020

DeepMPCVS: Deep Model Predictive Control for Visual Servoing

Pushkal Katara, Harish YVS, Harit Pandya, Abhinav Gupta, AadilMehdi Sanchawala, Gourav Kumar +2
CoRL 2020

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, attaining precise alignment for unseen environments pose a challenge to existing visual servoing approaches. While classical ap

Cited by 0Source ↗PDF ↗code ↗Scholar ↗