3 citations · 5 across the 20 of their papers we have counts for
19 papers · 1 filter
Multi-Rate Nonlinear Model Predictive Control for Wall-Supported Bipedal Locomotion of Quadrupedal Robots
Taizoon Chunawala, Jeeseop Kim, Kaveh Akbari Hamed
This paper presents a novel layered planning and control framework based on multi-rate nonlinear model predictive control (MR-NMPC) that enables quadrupedal robots to perform hybri…
ADMM-Based Distributed MPC with Control Barrier Functions for Safe Multi-Robot Quadrupedal Locomotion
Yicheng Zeng, Ruturaj S. Sambhus, Basit Muhammad Imran +3
This paper proposes a fully decentralized model predictive control (MPC) framework with control barrier function (CBF) constraints for safety-critical trajectory planning in multi-…
Hybrid Data-Driven Predictive Control for Robust and Reactive Exoskeleton Locomotion Synthesis
Kejun Li, Jeeseop Kim, Maxime Brunet +3
Robust bipedal locomotion in exoskeletons requires the ability to dynamically react to changes in the environment in real time. This paper introduces the hybrid data-driven predict…
A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots with Non-Negligible Manipulator Dynamics
Ruturaj Sambhus, Kapi Ketan Mehta, Ali MirMohammad Sadeghi +6
Model predictive control (MPC) combined with reduced-order template models has emerged as a powerful tool for trajectory optimization in dynamic legged locomotion. However, loco-ma…
Safety-Critical and Distributed Nonlinear Predictive Controllers for Teams of Quadrupedal Robots
Basit Muhammad Imran, Jeeseop Kim, Taizoon Chunawala +2
This paper presents a novel hierarchical, safety-critical control framework that integrates distributed nonlinear model predictive controllers (DNMPCs) with control barrier functio…
Robust Adaptive Safe Robotic Grasping with Tactile Sensing
Yitaek Kim, Jeeseop Kim, Albert H. Li +2
Robotic grasping requires safe force interaction to prevent a grasped object from being damaged or slipping out of the hand. In this vein, this paper proposes an integrated framewo…
Safety-critical Locomotion of Biped Robots in Infeasible Paths: Overcoming Obstacles during Navigation toward Destination
Jaemin Lee, Min Dai, Jeeseop Kim +1
This paper proposes a safety-critical locomotion control framework employed for legged robots exploring through infeasible path in obstacle-rich environments. Our research focus is…
Dynamic Walking on Highly Underactuated Point Foot Humanoids: Closing the Loop between HZD and HLIP
Adrian B. Ghansah, Jeeseop Kim, Kejun Li +1
Realizing bipedal locomotion on humanoid robots with point feet is especially challenging due to their highly underactuated nature, high degrees of freedom, and hybrid dynamics res…
Safety-critical Autonomous Inspection of Distillation Columns using Quadrupedal Robots Equipped with Roller Arms
Jaemin Lee, Jeeseop Kim, Aaron D. Ames
This paper proposes a comprehensive framework designed for the autonomous inspection of complex environments, with a specific focus on multi-tiered settings such as distillation co…
Data-Driven Predictive Control for Robust Exoskeleton Locomotion
Kejun Li, Jeeseop Kim, Xiaobin Xiong +3
Exoskeleton locomotion must be robust while being adaptive to different users with and without payloads. To address these challenges, this work introduces a data-driven predictive…
Safety-Critical Coordination of Legged Robots via Layered Controllers and Forward Reachable Set based Control Barrier Functions
Jeeseop Kim, Jaemin Lee, Aaron D. Ames
This paper presents a safety-critical approach to the coordination of robots in dynamic environments. To this end, we leverage control barrier functions (CBFs) with the forward rea…
A Data-driven Method for Safety-critical Control: Designing Control Barrier Functions from State Constraints
Jaemin Lee, Jeeseop Kim, Aaron D. Ames
This paper addresses the challenge of integrating explicit hard constraints into the control barrier function (CBF) framework for ensuring safety in autonomous systems, including r…
Safety-critical Control of Quadrupedal Robots with Rolling Arms for Autonomous Inspection of Complex Environments
Jaemin Lee, Jeeseop Kim, Wyatt Ubellacker +2
This paper presents a safety-critical control framework tailored for quadruped robots equipped with a roller arm, particularly when performing locomotive tasks such as autonomous r…
Humanoid Robot Co-Design: Coupling Hardware Design with Gait Generation via Hybrid Zero Dynamics
Adrian B. Ghansah, Jeeseop Kim, Maegan Tucker +1
Selecting robot design parameters can be challenging since these parameters are often coupled with the performance of the controller and, therefore, the resulting capabilities of t…
Hierarchical Relaxation of Safety-critical Controllers: Mitigating Contradictory Safety Conditions with Application to Quadruped Robots
Jaemin Lee, Jeeseop Kim, Aaron D. Ames
The safety-critical control of robotic systems often must account for multiple, potentially conflicting, safety constraints. This paper proposes novel relaxation techniques to addr…
Safety-Critical Coordination for Cooperative Legged Locomotion via Control Barrier Functions
Jeeseop Kim, Jaemin Lee, Aaron D. Ames
This paper presents a safety-critical approach to the coordinated control of cooperative robots locomoting in the presence of fixed (holonomic) constraints. To this end, we leverag…
Distributed Data-Driven Predictive Control for Multi-Agent Collaborative Legged Locomotion
Randall T Fawcett, Leila Amanzadeh, Jeeseop Kim +2
The aim of this work is to define a planner that enables robust legged locomotion for complex multi-agent systems consisting of several holonomically constrained quadrupeds. To thi…
Layered Control for Cooperative Locomotion of Two Quadrupedal Robots: Centralized and Distributed Approaches
Jeeseop Kim, Randall T Fawcett, Vinay R Kamidi +2
This paper presents a layered control approach for real-time trajectory planning and control of robust cooperative locomotion by two holonomically constrained quadrupedal robots. A…
Quadrupedal Locomotion via Event-Based Predictive Control and QP-Based Virtual Constraints
Kaveh Akbari Hamed, Jeeseop Kim, Abhishek Pandala
This paper aims to develop a hierarchical nonlinear control algorithm, based on model predictive control (MPC), quadratic programming (QP), and virtual constraints, to generate and…