A novel, open-source system has the ability to streamline disaster recovery and parcel delivery by rapidly generating a smooth path plan that cuts travel time and avoids obstacles.
2 min. read
In the aftermath of an earthquake, unpiloted aerial vehicles (UAVs) could fly through a collapsed building to map the scene, giving rescuers information they need to quickly reach survivors.
But this remains an extremely challenging problem for an autonomous robot, which would need to swiftly adjust its trajectory to avoid sudden obstacles while staying on course.
Researchers from Penn’s School of Engineering and Applied Science and MIT have developed a new trajectory-planning system that enables a UAV to react to obstacles in milliseconds while staying on a smooth flight path that minimizes travel time.
Their system uses a new mathematical formulation that ensures the robot travels safely to its destination along a feasible path, and that is less computationally intensive than other techniques. In this way, it generates smoother trajectories faster than state-of-the-art methods.
Named MIGHTY, the open-source system does not require proprietary software packages that can cost hundreds of thousands of dollars, and could be more readily deployed.
Yuwei Wu, a graduate student at Penn Engineering and Vijay Kumar, the Nemirovsky Family Dean of Penn Engineering are two co-authors of the paper, published in IEEE Robotics and Automation Letters.
MIGHTY uses a mathematical technique, called a Hermite spline, that optimizes the travel time and flight path together, in a single step, to form a smooth trajectory that can be precisely controlled. The researchers used a clever technique to reduce computational overhead: Instead of generating a trajectory from scratch each time, MIGHTY makes an initial guess of a trajectory. Then it refines the trajectory through an iterative optimization, using a map of the scene generated by the UAV’s lidar sensors.
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