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Pushkal Katara

5 accepted papers

2026

DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction Via Guided Diffusion

ICRA 2026poster

We introduce DreamControl, a novel methodology for learning autonomous whole-body humanoid skills. DreamControl leverages the strengths of diffusion models and Reinforcement Learning (RL): our core innovation is the use of a diffusion prior trained on human motion data, which subsequently guides an …

2024

ODIN: A Single Model for 2D and 3D Segmentation

CVPR 2024highlight

State-of-the-art models on contemporary 3D segmentation benchmarks like ScanNet consume and label dataset-provided 3D point clouds obtained through post processing of sensed multiview RGB-D images. They are typically trained in-domain forego large-scale 2D pre-training and outperform alternatives th…

2021

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

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 6SourceScholar
2020

DeepMPCVS: Deep Model Predictive Control for Visual Servoing

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