Safe Navigation in Human Occupied Environments Using Sampling and Control Barrier Functions
- Resource Type
- Conference
- Authors
- Majd, Keyvan; Yaghoubi, Shakiba; Yamaguchi, Tomoya; Hoxha, Bardh; Prokhorov, Danil; Fainekos, Georgios
- Source
- 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Intelligent Robots and Systems (IROS), 2021 IEEE/RSJ International Conference on. :5794-5800 Sep, 2021
- Subject
- Robotics and Control Systems
Navigation
Simulation
Dynamics
Predictive models
Intelligent robots
- Language
- ISSN
- 2153-0866
Sampling-based methods such as Rapidly-exploring Random Trees (RRTs) have been widely used for generating motion paths for autonomous mobile systems. In this work, we extend time-based RRTs with Control Barrier Functions (CBFs) to generate, safe motion plans in dynamic environments with many pedestrians. Our framework is based upon a human motion prediction model which is well suited for indoor narrow environments. We demonstrate our approach on a high-fidelity model of the Toyota Human Support Robot navigating in narrow corridors. We show in simulation results that our proposed online method can navigate safely in the presence of moving agents with unknown dynamics.