7 accepted papers
Heterogeneous robot teams executing Linear Temporal Logic (LTL) missions are usually modeled with fixed robot capabilities. In practice, capabilities may change during execution through tool acquisition, sensor activation, or module reconfiguration, making previously infeasible tasks executable and
Reactive planning enables the robots to deal with dynamic events in uncertain environments. However, existing methods heavily rely on the predefined hard-coded robot behaviors, e.g, a pre-coded temporal logic formula that specifies how robot should react. Little attention has been paid for autonomou…
This work develops a fast mission planning framework named planning decision tree (PDT), that can handle large-scale multi-robot systems with temporal logic specifications in real time. Specifically, PDT builds a tree incrementally to represent the task progress. The system states are modeled by bot
Empowering legged robots with agile maneuvers is a great challenge. While existing works have proposed diverse control-based and learning-based methods, it remains an open problem to endow robots with animal-like perception and athleticism. Towards this goal, we develop an End-to-End Legged Percepti…
This works exploits soft constraints in linear temporal logic task planning to enhance the agent’s capability in handling potentially conflicting or even infeasible tasks. Different from most existing works that focus on sticking to the original plan and trying to find a relaxed plan if the workspac…
Fast motion planning is of great significance, espe-cially when a timely mission is desired. However, the complexity of motion planning can grow drastically with the increase of environment details and mission complexity. This challenge can be further exacerbated if the tasks are coupled with the de…
In this letter, we present a transformer-based architecture, namely TF-Grasp, for robotic grasp detection. The developed TF-Grasp framework has two elaborate designs making it well suitable for visual grasping tasks. The first key design is that we adopt the local window attention to capture local c