78 citations · 309 across the 22 of their papers we have counts for
23 papers · 1 filter
MOSAIC-SV: Real-Time Adaptive Identification of Vessel Dynamics for the Control and Deployment of Aquatic Robots
Wensen Liu, Jerry Peng, Shravani Vedagiri +1
Model-based control of an aquatic robotic platform depends on a hydrodynamic model that is costly to identify and specific to the hull, payload, and conditions it was measured in.…
The Simplest Walking Robot: A bipedal robot with one actuator and two rigid bodies
James Kyle, Justin K. Yim, Kendall Hart +2
We present the design and experimental results of the first 1-DOF, hip-actuated bipedal robot. While passive dynamic walking is simple by nature, many existing bipeds inspired by t…
Saltation Matrices: The Essential Tool for Linearizing Hybrid Dynamical Systems
Nathan J. Kong, J. Joe Payne, James Zhu +1
Hybrid dynamical systems, i.e. systems that have both continuous and discrete states, are ubiquitous in engineering, but are difficult to work with due to their discontinuous trans…
Staged Contact Optimization: Combining Contact-Implicit and Multi-Phase Hybrid Trajectory Optimization
Michael R. Turski, Joseph Norby, Aaron M. Johnson
Trajectory optimization problems for legged robots are commonly formulated with fixed contact schedules. These multi-phase Hybrid Trajectory Optimization (HTO) methods result in lo…
Proprioception and reaction for walking among entanglements
Justin K. Yim, Jiming Ren, David Ologan +2
Entanglements like vines and branches in natural settings or cords and pipes in human spaces prevent mobile robots from accessing many environments. Legged robots should be effecti…
Grounding Robot Navigation in Self-Defense Law
James Zhu, Anoushka Shrivastava, Aaron M. Johnson
Robots operating in close proximity to humans rely heavily on human trust to successfully complete their tasks. But what are the real outcomes when this trust is violated? Self-def…
Convergent iLQR for Safe Trajectory Planning and Control of Legged Robots
James Zhu, J. Joe Payne, Aaron M. Johnson
In order to perform highly dynamic and agile maneuvers, legged robots typically spend time in underactuated domains (e.g. with feet off the ground) where the system has limited com…
Proprioception and Tail Control Enable Extreme Terrain Traversal by Quadruped Robots
Yanhao Yang, Joseph Norby, Justin K. Yim +1
Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, uncertainty coupled with contact discontinuities can lead to failu…
Conflict-Based Model Predictive Control for Scalable Multi-Robot Motion Planning
Ardalan Tajbakhsh, Lorenz T. Biegler, Aaron M. Johnson
This paper presents a scalable multi-robot motion planning algorithm called Conflict-Based Model Predictive Control (CB-MPC). Inspired by Conflict-Based Search (CBS), the planner l…
Reacting to Contact: Transparency and Collision Reflex in Actuation
Ankit Bhatia, Matthew T. Mason, Aaron M. Johnson
In unstructured environments, robots run the risk of unexpected collisions. How well they react to these events is determined by how transparent they are to collisions. Transparenc…
Adaptive Complexity Model Predictive Control
Joseph Norby, Ardalan Tajbakhsh, Yanhao Yang +1
This work introduces a formulation of model predictive control (MPC) which adaptively reasons about the complexity of the model based on the task while maintaining feasibility and…
Environmental Sampling with the Boustrophedon Decomposition Algorithm
Hannah He, Joe Norby, Sean Wang +4
The automation of data collection via mobile robots holds promise for increasing the efficacy of environmental investigations, but requires the system to autonomously determine how…
Hybrid iLQR Model Predictive Control for Contact Implicit Stabilization on Legged Robots
Nathan J. Kong, Chuanzheng Li, Aaron M. Johnson
Model Predictive Control (MPC) is a popular strategy for controlling robots but is difficult for systems with contact due to the complex nature of hybrid dynamics. To implement MPC…
TartanDrive: A Large-Scale Dataset for Learning Off-Road Dynamics Models
Samuel Triest, Matthew Sivaprakasam, Sean J. Wang +3
We present TartanDrive, a large scale dataset for learning dynamics models for off-road driving. We collected a dataset of roughly 200,000 off-road driving interactions on a modifi…
The Uncertainty Aware Salted Kalman Filter: State Estimation for Hybrid Systems with Uncertain Guards
J. Joe Payne, Nathan J. Kong, Aaron M. Johnson
In this paper we present a method for updating robotic state belief through contact with uncertain surfaces and apply this update to a Kalman filter for more accurate state estimat…
Hybrid Event Shaping to Stabilize Periodic Hybrid Orbits
James Zhu, Nathan J. Kong, George Council +1
Many controllers for legged robotic systems leverage open- or closed-loop control at discrete hybrid events to enhance stability. These controllers appear in several well studied p…
iLQR for Piecewise-Smooth Hybrid Dynamical Systems
Nathan J. Kong, George Council, Aaron M. Johnson
Trajectory optimization is a popular strategy for planning trajectories for robotic systems. However, many robotic tasks require changing contact conditions, which is difficult due…
The Salted Kalman Filter: Kalman Filtering on Hybrid Dynamical Systems
Nathan J. Kong, J. Joe Payne, George Council +1
Many state estimation and control algorithms require knowledge of how probability distributions propagate through dynamical systems. However, despite hybrid dynamical systems becom…
Developing a Simple Model for Sand-Tool Interaction and Autonomously Shaping Sand
Wooshik Kim, Catherine Pavlov, Aaron M. Johnson
Autonomy for robots interacting with sand will enable a wide range of beneficial behaviors, from earth moving for construction and farming vehicles to navigating rough terrain for…
Contact-Implicit Trajectory Optimization using Orthogonal Collocation
Amir Patel, Stacey Shield, Saif Kazi +2
In this paper we propose a method to improve the accuracy of trajectory optimization for dynamic robots with intermittent contact by using orthogonal collocation. Until recently, m…
Unsupervised Learning for Nonlinear PieceWise Smooth Hybrid Systems
Gilwoo Lee, Zita Marinho, Aaron M. Johnson +3
This paper introduces a novel system identification and tracking method for PieceWise Smooth (PWS) nonlinear stochastic hybrid systems. We are able to correctly identify and track…
Comparative Design, Scaling, and Control of Appendages for Inertial Reorientation
Thomas Libby, Aaron M. Johnson, Evan Chang-Siu +2
This paper develops a comparative framework for the design of actuated inertial appendages for planar, aerial reorientation. We define the Inertial Reorientation template, the simp…
A Hybrid Systems Model for Simple Manipulation and Self-Manipulation Systems
Aaron M. Johnson, Samuel A. Burden, Daniel E. Koditschek
Rigid bodies, plastic impact, persistent contact, Coulomb friction, and massless limbs are ubiquitous simplifications introduced to reduce the complexity of mechanics models despit…