research
∙
09/15/2023
The Fractal Hand-II: Reviving a Classic Mechanism for Contemporary Grasping Challenges
This paper, and its companion, propose a new fractal robotic gripper, dr...
share
research
∙
03/07/2023
An Active Learning Based Robot Kinematic Calibration Framework Using Gaussian Processes
Future NASA lander missions to icy moons will require completely automat...
research
∙
03/02/2023
STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation; Results from the DARPA Subterranean Challenge
Although autonomy has gained widespread usage in structured and controll...
research
∙
02/27/2023
FRoGGeR: Fast Robust Grasp Generation via the Min-Weight Metric
Many approaches to grasp synthesis optimize analytic quality metrics tha...
research
∙
12/12/2022
Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data
Recent advances in safety-critical risk-aware control are predicated on ...
research
∙
12/01/2022
Adaptive Conformal Prediction for Motion Planning among Dynamic Agents
This paper proposes an algorithm for motion planning among dynamic agent...
research
∙
04/21/2022
Sample-Based Bounds for Coherent Risk Measures: Applications to Policy Synthesis and Verification
The dramatic increase of autonomous systems subject to variable environm...
research
∙
04/20/2022
Risk-Averse Receding Horizon Motion Planning
This paper studies the problem of risk-averse receding horizon motion pl...
research
∙
03/25/2022
Moving Obstacle Avoidance: a Data-Driven Risk-Aware Approach
This paper proposes a new structured method for a moving agent to predic...
research
∙
03/22/2022
Distributionally Robust Model Predictive Control with Total Variation Distance
This paper studies the problem of distributionally robust model predicti...
research
∙
10/20/2021
Quadrotor Trajectory Tracking with Learned Dynamics: Joint Koopman-based Learning of System Models and Function Dictionaries
Nonlinear dynamical effects are crucial to the operation of many agile r...
research
∙
05/17/2021
Koopman NMPC: Koopman-based Learning and Nonlinear Model Predictive Control of Control-affine Systems
Koopman-based learning methods can potentially be practical and powerful...
research
∙
03/26/2021
Risk-Averse Stochastic Shortest Path Planning
We consider the stochastic shortest path planning problem in MDPs, i.e.,...
research
∙
03/05/2021
Limits of Probabilistic Safety Guarantees when Considering Human Uncertainty
When autonomous robots interact with humans, such as during autonomous d...
research
∙
02/18/2021
Learning Invariant Representation of Tasks for Robust Surgical State Estimation
Surgical state estimators in robot-assisted surgery (RAS) - especially t...
research
∙
11/23/2020
Risk-Sensitive Motion Planning using Entropic Value-at-Risk
We consider the problem of risk-sensitive motion planning in the presenc...
research
∙
11/09/2020
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes
Characterizing what types of exoskeleton gaits are comfortable for users...
research
∙
09/24/2020
daVinciNet: Joint Prediction of Motion and Surgical State in Robot-Assisted Surgery
This paper presents a technique to concurrently and jointly predict the ...
research
∙
04/11/2020
Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties
Robots operating in real world settings must navigate and maintain safet...
research
∙
03/19/2020
Barrier Functions for Multiagent-POMDPs with DTL Specifications
Multi-agent partially observable Markov decision processes (MPOMDPs) pro...
research
∙
03/13/2020
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits
Understanding users' gait preferences of a lower-body exoskeleton requir...
research
∙
02/07/2020
Temporal Segmentation of Surgical Sub-tasks through Deep Learning with Multiple Data Sources
Many tasks in robot-assisted surgeries (RAS) can be represented by finit...
research
∙
01/21/2020
Stochastic Finite State Control of POMDPs with LTL Specifications
Partially observable Markov decision processes (POMDPs) provide a modeli...
research
∙
09/23/2019
Optimal Motion Planning for Multi-Modal Hybrid Locomotion
Hybrid locomotion, which combines multiple modalities of locomotion with...
research
∙
08/04/2019
Dueling Posterior Sampling for Preference-Based Reinforcement Learning
In preference-based reinforcement learning (RL), an agent interacts with...
research
∙
05/14/2019
Control Regularization for Reduced Variance Reinforcement Learning
Dealing with high variance is a significant challenge in model-free rein...
research
∙
03/21/2019
End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks
Reinforcement Learning (RL) algorithms have found limited success beyond...
research
∙
03/19/2019
Safe Policy Synthesis in Multi-Agent POMDPs via Discrete-Time Barrier Functions
A multi-agent partially observable Markov decision process (MPOMDP) is a...
research
∙
06/20/2018
Stagewise Safe Bayesian Optimization with Gaussian Processes
Enforcing safety is a key aspect of many problems pertaining to sequenti...
research
∙
11/21/2017
Quantifying Performance of Bipedal Standing with Multi-channel EMG
Spinal cord stimulation has enabled humans with motor complete spinal co...
research
∙
10/07/2017
Meta Inverse Reinforcement Learning via Maximum Reward Sharing for Human Motion Analysis
This work handles the inverse reinforcement learning (IRL) problem where...
research
∙
07/22/2017
Clinical Patient Tracking in the Presence of Transient and Permanent Occlusions via Geodesic Feature
This paper develops a method to use RGB-D cameras to track the motions o...
research
∙
01/15/2014