Researchers at the Indian Institute of Technology (IIT), Madras have developed a class of fast and efficient “motion planning” algorithms that can think like humans and help autonomous air, ground or surface vehicles navigate obstacle-disrupted environments, make capable.
Novel calculation of “safe” area:
Unmanned Aerial Vehicles (UAVs) are often deployed to survey affected areas and scan debris for search and rescue missions. Since in such applications, UAV paths need to be planned in advance in a time-critical manner, these algorithms could play an important role, he said.
Strong Applicability of GSE-Based Algorithms:
The researcher explained that the main advantage of GSE-based algorithms over many other well-established motion planning algorithms lies in the significant improvement of computational efficiency. This naturally leads to strong applicability of GSE-based algorithms in applications where planning is time-sensitive.
This, in essence, significantly improves the search speed of the environment by requiring only very few iterations of the GSE-based algorithm to connect the initial and target regions. Explaining the applications of “MOTION PLANNING” algorithms, S Ghosh, Assistant Professor, Department of Aerospace Engineering, IIT Madras said, – Drones equipped with our algorithms can be of major use during disaster management and response scenarios.
Maximum representation of free space:
Rather than using a computationally heavy dedicated collision detection module, these algorithms take advantage of the novel notion of ‘normalized size’, which gives the maximum representation of free space that is accessible from a point in the environment, approximately equal to that of a human. The notion about a ‘safe’ place to move around is similar to that of A. Rajkumar.
In the wake of a disaster event such as an earthquake, UAVs are often deployed to survey the affected areas and scan debris for search and rescue missions. Since such applications need to plan UAV paths in advance in a time-critical manner, our algorithms can play an important role,” he said.
To strategize coordinated motion in a multi-vehicle set-up:
