In recent years, formal methods have been extensively used in the design of autonomous
systems. By employing mathematically rigorous techniques, formal methods can provide …

Contact is at the core of robotic manipulation. At times, it is desired (eg manipulation and
grasping), and at times, it is harmful (eg when avoiding obstacles). However, traditional path …

Ensuring safety in human–robot collaboration is one of the main challenges in mobile
robotics today. Semantic maps are a potential solution because they provide semantic …

Temporal logic is a concise way of specifying complex tasks. However, motion planning to
achieve temporal logic specifications is difficult, and existing methods struggle to scale to …

This paper addresses a new semantic multi-robot planning problem in uncertain and
dynamic environments. Particularly, the environment is occupied with mobile and uncertain …

The availability of real-time semantics greatly improves the core geometric functionality of
SLAM systems, enabling numerous robotic and AR/VR applications. We present a new …

We consider perception-based control using state estimates that are obtained from high-
dimensional sensor measurements via learning-enabled perception maps. However, these …

Reinforcement learning (RL) with linear temporal logic (LTL) objectives can allow robots to
carry out symbolic event plans in unknown environments. Most existing methods assume …

This work presents a step towards utilizing incrementally-improving symbolic perception
knowledge of the robot's surroundings for provably correct reactive control synthesis applied …

Multi-camera-based simultaneous localization and mapping (SLAM) has been widely
applied in various mobile robots under uncertain or unknown environments to accomplish …