Robotic Odor Source Localization with AI Methods
Robotic odor source localization is a technology that enables a mobile robot or autonomous agent to locate hidden odor sources in unknown environments. This approach has significant potential for replacing human searchers in hazardous situations, such as detecting chemical leaks or gas emissions. The key challenge lies in designing effective navigation algorithms that allow the robot to respond appropriately to sensory inputs. This presentation explores various olfactory-based navigation strategies, including AI-driven algorithms and semantic navigation approaches that fuse visual and olfactory data. The presentation also highlights real-world applications that demonstrate the capabilities and impact of robotic odor source localization systems.
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- Date: 02 Jun 2025
- Time: 04:00 PM UTC to 05:00 PM UTC
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- Starts 21 May 2025 07:00 PM UTC
- Ends 30 May 2025 05:00 AM UTC
- No Admission Charge
Speakers
Dr. Wang of Louisiana Tech University
Robotic Odor Source Localization with AI Methods
Robotic odor source localization is a technology that enables a mobile robot or autonomous agent to locate hidden odor sources in unknown environments. This approach has significant potential for replacing human searchers in hazardous situations, such as detecting chemical leaks or gas emissions. The key challenge lies in designing effective navigation algorithms that allow the robot to respond appropriately to sensory inputs. This presentation explores various olfactory-based navigation strategies, including AI-driven algorithms and semantic navigation approaches that fuse visual and olfactory data. This presentation also highlights real-world applications that demonstrate the capabilities and impact of robotic odor source localization systems.
Biography:
Dr. Lingxiao Wang is an Assistant Professor of Electrical Engineering at Louisiana Tech University. He earned his Ph.D. in Electrical Engineering and Computer Science in 2021 and his M.S. in Electrical and Computer Engineering in 2018, both from Embry-Riddle Aeronautical University. His research interests include robotics, autonomous systems, and artificial intelligence, with a particular focus on developing intelligent decision-making systems for controlling and navigating robots in dynamic environments.