activity
20202025
most citedPick and Place Planning is Better than Pick Planning then Place Planning

7 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2025

First Plan Then Evaluate: Multi-Target Planning with Post-Planning Success Evaluation Improves Learning-Based Grasping Pipelines

Martin Matak, Mohanraj Devendran Shanthi, Karl Van Wyk +1

Autonomous multi-finger grasping is a fundamental capability in robotic manipulation. Optimization-based approaches show strong performance, but tend to be sensitive to initializat…

cs.RO2025

Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference

Yixuan Huang, Novella Alvina, Mohanraj Devendran Shanthi +1

Skill effect models for long-horizon manipulation tasks are prone to failures in conditions not covered by training data distributions. Therefore, enabling robots to reason about a…

cs.RO2025

DiffDef: A Diffusion Model for Generating Multimodal Goal Shapes From Demonstrations for Deformable Object Manipulation

Bao Thach, Tanner Watts, Siyeon Kim +6

Deformable object manipulation is a key capability in many robotic applications. A promising paradigm for this problem is shape servoing, which aims to control deformable objects t…

cs.RO2024★ 7 cited

Pick and Place Planning is Better than Pick Planning then Place Planning

Mohanraj Devendran Shanthi, Tucker Hermans

Robotic pick and place stands at the heart of autonomous manipulation. When conducted in cluttered or complex environments robots must jointly reason about the selected grasp and d…

cs.RO2020

Comparing Piezoresistive Substrates for Tactile Sensing in Dexterous Hands

Rebecca Miles, Martin Matak, Sarah Hood +3

While tactile skins have been shown to be useful for detecting collisions between a robotic arm and its environment, they have not been extensively used for improving robotic grasp…