Differential Dynamic Programming (DDP) is an efficient computational too...
We present CAJun, a novel hierarchical learning and control framework th...
This paper presents a comprehensive benchmarking suite tailored to offli...
Large language models (LLMs) have demonstrated exciting progress in acqu...
Animals have evolved various agile locomotion strategies, such as sprint...
We present IndoorSim-to-OutdoorReal (I2O), an end-to-end learned visual
...
Jumping is essential for legged robots to traverse through difficult
ter...
Safe reinforcement learning (RL) trains a constraint satisfaction policy...
Training complex machine learning (ML) architectures requires a compute ...
We propose a framework to enable multipurpose assistive mobile robots to...
Specialized motions such as jumping are often achieved on quadruped robo...
Reinforcement Learning (RL) has witnessed great strides for quadruped
lo...
Despite decades of research, existing navigation systems still face
real...
As robots increasingly enter human-centered environments, they must not ...
The BARN (Benchmark Autonomous Robot Navigation) Challenge took place at...
Evolution Strategy (ES) algorithms have shown promising results in train...
The semantics of the environment, such as the terrain type and property,...
Training a high-dimensional simulated agent with an under-specified rewa...
Designing control policies for legged locomotion is complex due to the
u...
We focus on the problem of developing efficient controllers for quadrupe...
As learning-based approaches progress towards automating robot controlle...
Reproducing the diverse and agile locomotion skills of animals has been ...
Decentralized multiagent planning raises many challenges, such as adapti...
We propose an architecture for learning complex controllable behaviors b...
Imitation learning is a popular approach for training effective visual
n...
We present a model-based framework for robot locomotion that achieves wa...
Designing agile locomotion for quadruped robots often requires extensive...