research
∙
01/17/2023
Tactile Tool Manipulation
Humans can effortlessly perform very complex, dexterous manipulation tas...
share
research
∙
09/07/2022
Real-to-Sim: Deep Learning with Auto-Tuning to Predict Residual Errors using Sparse Data
Achieving highly accurate kinematic or simulator models that are close t...
research
∙
08/24/2022
Feasibility Study of LIMMS, A Multi-Agent Modular Robotic Delivery System with Various Locomotion and Manipulation Modes
The logistics of transporting a package from a storage facility to the c...
research
∙
07/31/2022
Multi-Modal Multi-Agent Optimization for LIMMS, A Modular Robotics Approach to Delivery Automation
In this paper we present a motion planner for LIMMS, a modular multi-age...
research
∙
07/16/2022
Learning Near-global-optimal Strategies for Hybrid Non-convex Model Predictive Control of Single Rigid Body Locomotion
Convex model predictive controls (MPCs) with a single rigid body model h...
research
∙
07/04/2022
Simultaneous Contact-Rich Grasping and Locomotion via Distributed Optimization Enabling Free-Climbing for Multi-Limbed Robots
While motion planning of locomotion for legged robots has shown great su...
research
∙
07/04/2022
SCALER: A Tough Versatile Quadruped Free-Climber Robot
This paper introduces SCALER, a quadrupedal robot that demonstrates clim...
research
∙
07/03/2022
Auto-Calibrating Admittance Controller for Robust Motion of Robotic Systems
We demonstrate an admittance controller with auto-tuning that can be app...
research
∙
09/30/2021
An Under-Actuated Whippletree Mechanism Gripper based on Multi-Objective Design Optimization with Auto-Tuned Weights
Current rigid linkage grippers are limited in flexibility, and gripper d...
research
∙
09/14/2021
Designing Multi-Stage Coupled Convex Programming with Data-Driven McCormick Envelope Relaxations for Motion Planning
For multi-limbed robots, motion planning with posture and force constrai...
research
∙
08/03/2021
SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous Robots
We present an end-to-end online motion planning framework that uses a da...
research
∙
03/01/2021
LTO: Lazy Trajectory Optimization with Graph-Search Planning for High DOF Robots in Cluttered Environments
Although Trajectory Optimization (TO) is one of the most powerful motion...
research
∙
07/28/2020
Risk-Averse MPC via Visual-Inertial Input and Recurrent Networks for Online Collision Avoidance
In this paper, we propose an online path planning architecture that exte...
research
∙
06/04/2020
Risk-Aware Motion Planning for a Limbed Robot with Stochastic Gripping Forces Using Nonlinear Programming
We present a motion planning algorithm with probabilistic guarantees for...
research
∙
02/23/2020
Deep Reinforcement Learning with Linear Quadratic Regulator Regions
Practitioners often rely on compute-intensive domain randomization to en...
research
∙
01/22/2020