Richard Hawkins
Papers
3
Total Citations
173
H-Index
2
About
Richard Hawkins is a leading researcher in the safe deployment of autonomous systems, with a primary focus on drone navigation, robotics, and the robustness of AI-driven perception. His most impactful work, "Deep reinforcement learning for drone navigation using sensor data" (2020), has garnered 169 citations, establishing a foundational approach for using reinforcement learning to enable unmanned aerial vehicles to navigate complex environments using real-time sensor inputs. This work is pivotal for applications in surveillance, infrastructure monitoring, and data collection, where accurate and multifaceted sensing is critical for early problem detection. More recently, Hawkins has advanced the field of safety assurance for autonomous systems. His 2024 paper, "Defining an Effective Context for the Safe Operation of Autonomous Systems," and his 2025 work, "Robustness Requirement Coverage using a Situation Coverage Approach for Vision-based AI Systems," tackle the critical challenge of ensuring that AI-based robots and vehicles operate safely amidst dynamic conditions and component degradation. By developing frameworks for situation coverage and robustness requirements, Hawkins is shaping how engineers validate vision-based AI, making autonomous systems more reliable and trustworthy in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Deep reinforcement learning for drone navigation using sensor data169 citations · 2020
- 2
- 3