Researchers at the Stanford Biomimetics and Dexterous Manipulation Laboratory have been working to develop a spy drone that can attach itself to walls for long periods of time in order to collect important images and data.
The goal for the researchers is to create drones that can be deployed both efficiently and cost effectively. The challenge has been to create a spy drone that can stay in the air for extended time, as most now can only stay hovering for approximately 10 minutes at a time, according to IEEE Spectrum. In order to remain in the sky longer and provide more useful data, this spy drone is designed to attach to walls and perch for what could be days at a time. By attaching to walls, this spy drone would be able to shut off its motors and expend its energy on collecting data instead. Micro grips on the drone allow it to adhere to these rough vertical surfaces.
What's Driving This Trend
- Wall-perching Drones
- Opportunity for disruptively innovating aerial surveillance with advanced grip mechanisms for extended data gathering on vertical surfaces.
- Long-range Drones
- Opportunity for disruptively innovating aerial surveillance with extended range capabilities for efficient and cost-effective deployment.
- Energy Efficient Drones
- Opportunity for disruptively innovating aerial surveillance with energy-efficient designs and shut-off mechanisms for prolonged time in the sky.
Who This Affects Most
- Security and Surveillance Industry
- Opportunity for disruptively innovating aerial data collection and surveillance with extended hovering time and advanced grip mechanisms for obtaining crucial data on vertical surfaces.
- Military and Defense Industry
- Opportunity for disruptively innovating aerial surveillance with extended-range capabilities and energy-efficient designs for cost-effective deployment and effective data gathering.
- Environmental Monitoring Industry
- Opportunity for disruptively innovating aerial data collection with energy-efficient designs and long-range capabilities to obtain crucial environmental data at an efficient cost.
