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Inspired by how ants visually recognize their environment and count their steps to navigate back home, MAVLab researchers have developed an insect-inspired navigation strategy for …
Inspired by how ants visually recognize their environment and count their steps to navigate back home, MAVLab researchers have developed an insect-inspired navigation strategy for …
In collaboration with ESA’s Advanced Concepts Team, we published our work on end-to-end guidance and control networks in the June 2024 issue of Science Robotics. …
Our work on fully neuromorphic vision and control for autonomous drone flight has been published in the Science Robotics May 2024 issue. In this work, …
The work from PhD candidate Liming Zheng and Assistant Professor Salua Hamaza from the BioMorphic Intelligence Lab was published in the journal of IEEE Robotics and Automation …
With an escalating demand for quadcopters in emergency response, inspection and delivery, the need for speed and energy efficiency is paramount. However, developing autonomous systems …
Birds display remarkable adaptability in harnessing their surroundings for efficient flight, exemplified by the ingenious behavior observed in Kestrels. These birds employ a unique technique …
At ICRA (IEEE International Conference on Robotics and Automation) 2023, MAVLab presented AvoidBench, a high-fidelity vision-based obstacle avoidance benchmarking suite for multi-rotors. Motivation Vision-based obstacle …
Researchers from MAVLab and collaborators have developed a new theory on how flying drones and insects can estimate the gravity direction. Whereas drones typically use …
Insect-inspired AI for autonomous robots Small autonomous mobile robots, such as drones, rovers, and legged robots, promise to perform a wide range of tasks, from …