252 citations · 689 across the 37 of their papers we have counts for
12 papers · 1 filter
A Unified Perspective on Multiple Shooting In Differential Dynamic Programming
He Li, Wenhao Yu, Tingnan Zhang +1
Differential Dynamic Programming (DDP) is an efficient computational tool for solving nonlinear optimal control problems. It was originally designed as a single shooting method and…
GeoGPT: Understanding and Processing Geospatial Tasks through An Autonomous GPT
Yifan Zhang, Cheng Wei, Shangyou Wu +2
Decision-makers in GIS need to combine a series of spatial algorithms and operations to solve geospatial tasks. For example, in the task of facility siting, the Buffer tool is usua…
Transforming a Quadruped into a Guide Robot for the Visually Impaired: Formalizing Wayfinding, Interaction Modeling, and Safety Mechanism
J. Taery Kim, Wenhao Yu, Yash Kothari +3
This paper explores the principles for transforming a quadrupedal robot into a guide robot for individuals with visual impairments. A guide robot has great potential to resolve the…
Datasets and Benchmarks for Offline Safe Reinforcement Learning
Zuxin Liu, Zijian Guo, Haohong Lin +8
This paper presents a comprehensive benchmarking suite tailored to offline safe reinforcement learning (RL) challenges, aiming to foster progress in the development and evaluation…
Language to Rewards for Robotic Skill Synthesis
Wenhao Yu, Nimrod Gileadi, Chuyuan Fu +17
Large language models (LLMs) have demonstrated exciting progress in acquiring diverse new capabilities through in-context learning, ranging from logical reasoning to code-writing.…
CAJun: Continuous Adaptive Jumping using a Learned Centroidal Controller
Yuxiang Yang, Guanya Shi, Xiangyun Meng +4
We present CAJun, a novel hierarchical learning and control framework that enables legged robots to jump continuously with adaptive jumping distances. CAJun consists of a high-leve…
SayTap: Language to Quadrupedal Locomotion
Yujin Tang, Wenhao Yu, Jie Tan +3
Large language models (LLMs) have demonstrated the potential to perform high-level planning. Yet, it remains a challenge for LLMs to comprehend low-level commands, such as joint an…
Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Ken Caluwaerts, Atil Iscen, J. Chase Kew +41
Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biol…
IndoorSim-to-OutdoorReal: Learning to Navigate Outdoors without any Outdoor Experience
Joanne Truong, April Zitkovich, Sonia Chernova +4
We present IndoorSim-to-OutdoorReal (I2O), an end-to-end learned visual navigation approach, trained solely in simulated short-range indoor environments, and demonstrates zero-shot…
Pre-training Language Models for Comparative Reasoning
Mengxia Yu, Zhihan Zhang, Wenhao Yu +1
Comparative reasoning is a process of comparing objects, concepts, or entities to draw conclusions, which constitutes a fundamental cognitive ability. In this paper, we propose a n…
Continuous Versatile Jumping Using Learned Action Residuals
Yuxiang Yang, Xiangyun Meng, Wenhao Yu +3
Jumping is essential for legged robots to traverse through difficult terrains. In this work, we propose a hierarchical framework that combines optimal control and reinforcement lea…
Constrained Decision Transformer for Offline Safe Reinforcement Learning
Zuxin Liu, Zijian Guo, Yihang Yao +4
Safe reinforcement learning (RL) trains a constraint satisfaction policy by interacting with the environment. We aim to tackle a more challenging problem: learning a safe policy fr…