1 citations · 3 across the 14 of their papers we have counts for
14 papers
Remember what you did?: Learning Behavioral Memories for Partially Observable Object Manipulation
Kuancheng Wang, Seungho Yeom, Jinglin Cao +3
Long horizon, contact-rich manipulation is inherently partially observable. This is as a single visual observation rarely captures a robot's full action context, including prior at…
Safe Stochastic Explorer: Enabling Safe Goal Driven Exploration in Stochastic Environments and Safe Interaction with Unknown Objects
Nikhil Uday Shinde, Dylan Hirsch, Michael C. Yip +1
Autonomous robots operating in unstructured, safety-critical environments, from planetary exploration to warehouses and homes, must learn to safely navigate and interact with their…
Learning to Nudge: A Scalable Barrier Function Framework for Safe Robot Interaction in Dense Clutter
Haixin Jin, Nikhil Uday Shinde, Soofiyan Atar +5
Robots operating in everyday environments must navigate and manipulate within densely cluttered spaces, where physical contact with surrounding objects is unavoidable. Traditional…
From Space to Time: Enabling Adaptive Safety with Learned Value Functions via Disturbance Recasting
Sander Tonkens, Nikhil Uday Shinde, Azra Begzadić +3
The widespread deployment of autonomous systems in safety-critical environments such as urban air mobility hinges on ensuring reliable, performant, and safe operation under varying…
Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations
William Sharpless, Dylan Hirsch, Sander Tonkens +2
Hard constraints in reinforcement learning (RL) often degrade policy performance. Lagrangian methods offer a way to blend objectives with constraints, but require intricate reward…
Back to Base: Towards Hands-Off Learning via Safe Resets with Reach-Avoid Safety Filters
Azra Begzadić, Nikhil Uday Shinde, Sander Tonkens +5
Designing controllers that accomplish tasks while guaranteeing safety constraints remains a significant challenge. We often want an agent to perform well in a nominal task, such as…
MEDiC: Autonomous Surgical Robotic Assistance to Maximizing Exposure for Dissection and Cautery
Xiao Liang, Chung-Pang Wang, Nikhil Uday Shinde +3
Surgical automation has the capability to improve the consistency of patient outcomes and broaden access to advanced surgical care in underprivileged communities. Shared autonomy,…
JIGGLE: An Active Sensing Framework for Boundary Parameters Estimation in Deformable Surgical Environments
Nikhil Uday Shinde, Xiao Liang, Fei Liu +4
Surgical automation can improve the accessibility and consistency of life saving procedures. Most surgeries require separating layers of tissue to access the surgical site, and sut…
SURESTEP: An Uncertainty-Aware Trajectory Optimization Framework to Enhance Visual Tool Tracking for Robust Surgical Automation
Nikhil U. Shinde, Zih-Yun Chiu, Florian Richter +4
Inaccurate tool localization is one of the main reasons for failures in automating surgical tasks. Imprecise robot kinematics and noisy observations caused by the poor visual acuit…
Robust Surgical Tool Tracking with Pixel-based Probabilities for Projected Geometric Primitives
Christopher D'Ambrosia, Florian Richter, Zih-Yun Chiu +4
Controlling robotic manipulators via visual feedback requires a known coordinate frame transformation between the robot and the camera. Uncertainties in mechanical systems as well…
Finding Biomechanically Safe Trajectories for Robot Manipulation of the Human Body in a Search and Rescue Scenario
Elizabeth Peiros, Zih-Yun Chiu, Yuheng Zhi +2
There has been increasing awareness of the difficulties in reaching and extracting people from mass casualty scenarios, such as those arising from natural disasters. While platform…
Object-centric Representations for Interactive Online Learning with Non-Parametric Methods
Nikhil U. Shinde, Jacob Johnson, Sylvia Herbert +1
Large offline learning-based models have enabled robots to successfully interact with objects for a wide variety of tasks. However, these models rely on fairly consistent structure…
Investigating Low Data, Confidence Aware Image Prediction on Smooth Repetitive Videos using Gaussian Processes
Nikhil U. Shinde, Xiao Liang, Florian Richter +1
The ability to predict future states is crucial to informed decision-making while interacting with dynamic environments. With cameras providing a prevalent and information-rich sen…
Koopman-Hopf Hamilton-Jacobi Reachability and Control
Will Sharpless, Nikhil Shinde, Matthew Kim +2
The Hopf formula for Hamilton-Jacobi reachability (HJR) analysis has been proposed to solve high-dimensional differential games, producing the set of initial states and correspondi…