218 citations · 396 across the 14 of their papers we have counts for
14 papers
Benchmarking Potential Based Rewards for Learning Humanoid Locomotion
Se Hwan Jeon, Steve Heim, Charles Khazoom +1
The main challenge in developing effective reinforcement learning (RL) pipelines is often the design and tuning the reward functions. Well-designed shaping reward can lead to signi…
Reinforcement Learning for Legged Robots: Motion Imitation from Model-Based Optimal Control
AJ Miller, Shamel Fahmi, Matthew Chignoli +1
We propose MIMOC: Motion Imitation from Model-Based Optimal Control. MIMOC is a Reinforcement Learning (RL) controller that learns agile locomotion by imitating reference trajector…
Design of a Multimodal Fingertip Sensor for Dynamic Manipulation
Andrew SaLoutos, Elijah Stanger-Jones, Menglong Guo +2
We introduce a spherical fingertip sensor for dynamic manipulation. It is based on barometric pressure and time-of-flight proximity sensors and is low-latency, compact, and physica…
Towards Robust Autonomous Grasping with Reflexes Using High-Bandwidth Sensing and Actuation
Andrew SaLoutos, Hongmin Kim, Elijah Stanger-Jones +2
Modern robotic manipulation systems fall short of human manipulation skills partly because they rely on closing feedback loops exclusively around vision data, which reduces system…
Fast Reflexive Grasping with a Proprioceptive Teleoperation Platform
Andrew SaLoutos, Elijah Stanger-Jones, Sangbae Kim
We present a proprioceptive teleoperation system that uses a reflexive grasping algorithm to enhance the speed and robustness of pick-and-place tasks. The system consists of two ma…
Humanoid Self-Collision Avoidance Using Whole-Body Control with Control Barrier Functions
Charles Khazoom, Daniel Gonzalez-Diaz, Yanran Ding +1
This work combines control barrier functions (CBFs) with a whole-body controller to enable self-collision avoidance for the MIT Humanoid. Existing reactive controllers for self-col…
Orientation-Aware Model Predictive Control with Footstep Adaptation for Dynamic Humanoid Walking
Yanran Ding, Charles Khazoom, Matthew Chignoli +1
This paper proposes a novel orientation-aware model predictive control (MPC) for dynamic humanoid walking that can plan footstep locations online. Instead of a point-mass model, th…
Rapid and Reliable Quadruped Motion Planning with Omnidirectional Jumping
Matthew Chignoli, Savva Morozov, Sangbae Kim
Dynamic jumping with legged robots poses a challenging problem in planning and control. Formulating the jump optimization to allow fast online execution is difficult; efficiently u…
Learning to Jump from Pixels
Gabriel B. Margolis, Tao Chen, Kartik Paigwar +4
Today's robotic quadruped systems can robustly walk over a diverse range of rough but continuous terrains, where the terrain elevation varies gradually. Locomotion on discontinuous…
Online Trajectory Optimization for Dynamic Aerial Motions of a Quadruped Robot
Matthew Chignoli, Sangbae Kim
This work presents a two part framework for online planning and execution of dynamic aerial motions on a quadruped robot. Motions are planned via a centroidal momentum-based nonlin…
Real-time Optimal Landing Control of the MIT Mini Cheetah
Se Hwan Jeon, Sangbae Kim, Donghyun Kim
Quadrupedal landing is a complex process involving large impacts, elaborate contact transitions, and is a crucial recovery behavior observed in many biological animals. This work p…
The MIT Humanoid Robot: Design, Motion Planning, and Control For Acrobatic Behaviors
Matthew Chignoli, Donghyun Kim, Elijah Stanger-Jones +1
Demonstrating acrobatic behavior of a humanoid robot such as flips and spinning jumps requires systematic approaches across hardware design, motion planning, and control. In this p…
Highly Dynamic Quadruped Locomotion via Whole-Body Impulse Control and Model Predictive Control
Donghyun Kim, Jared Di Carlo, Benjamin Katz +2
Dynamic legged locomotion is a challenging topic because of the lack of established control schemes which can handle aerial phases, short stance times, and high-speed leg swings. I…
Linear Matrix Inequalities for Physically-Consistent Inertial Parameter Identification: A Statistical Perspective on the Mass Distribution
Patrick M. Wensing, Sangbae Kim, Jean-Jacques Slotine
With the increased application of model-based whole-body control in legged robots, there has been a resurgence of research interest into methods for accurate system identification.…