Visual navigation has received significant attention recently. Most of the prior works focus on
predicting navigation actions based on semantic features extracted from visual encoders …

Controlling robots through natural language instructions in open-vocabulary scenarios is
pivotal for enhancing human-robot collaboration and complex robot behavior synthesis …

Reinforcement learning (RL) algorithms for continuous control tasks require accurate
sampling-based action selection. Many tasks, such as robotic manipulation, contain inherent …

Many manipulation tasks require the robot to rearrange objects relative to one another. Such
tasks can be described as a sequence of relative poses between parts of a set of rigid …

Learning navigation capabilities in different environments has long been one of the major
challenges in decision-making. In this work, we focus on zero-shot navigation ability using …

Obstacle detection and tracking represent a critical component in robot autonomous
navigation. In this paper, we propose ODTFormer, a Transformer-based model to address …

Robots are on the verge of becoming integral components of our domestic environments as
personal assistants. Although their present functions are confined to specific tasks within …

Controlling robots through natural language instructions in open-vocabulary scenarios is
pivotal for enhancing human-robot collaboration and complex robot behavior synthesis …

Learning for robot navigation presents a critical and challenging task. The scarcity and
costliness of real-world datasets necessitate efficient learning approaches. In this letter, we …