Researchers at IIT Madras Develop Motion Planning Algorithm

Researchers at IIT Madras Develop Motion Planning Algorithm that can think like humans
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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

Novel calculation of “safe” area:

    • 1) These approaches have been found to produce better results than many existing fundamental and state-of-the-art motion planning algorithms.
    • 2) The GSE-based algorithm works by computing a ‘safe’ zone consisting of large ‘visible’ areas in the environment, optimized to ensure navigability,” said V. Zinage, an IIT Madras alumnus.
    • 3) Because of its new calculation of the “safe” zone, it provides a significant advance during time-sensitive planning scenarios such as applications such as self-driving cars, disaster response, ISR operations, aerial drone delivery and planetary exploration. originates in. The team claimed
    • 4) Next, the algorithms select a random point in this ‘visible’ region and connect it through a secure ‘edge’ to the securely reachable areas discovered so far.
    • 5) Ultimately, the algorithm can almost always connect any two points in any environment that meets some basic criteria,” Zinez said.

(UAVs) are often deployed to survey the affected areas

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.

“Motion planning” algorithm

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 disaster event like earthquake

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.

Multi-Vehicle set-up

To strategize coordinated motion in a multi-vehicle set-up:

    • 1) The current state of this research, according to the team, is limited to the theoretical development and improvement of GSE-based algorithms and broadly realistic simulation-based validation of the same.
    • 2) Broadly speaking, the class of GSE-based algorithms has promising potential in autonomous applications such as warehouse material movement, inspection of project commissioning, drone delivery, disaster management, self-driving cars, and the like.
    • 3) These algorithms can also be leveraged for coordinated motion strategy in a multi-vehicle set-up,” he added.
    • 4) According to the team, the algorithm has been developed on a new notion of “GENERALIZED SIZE EXPANSION” (GSE) that enables planning of a safe and dynamically feasible trajectory for autonomous vehicles.
    • 5) Researchers are planning to apply these algorithms to unmanned aerial and ground vehicles in the near future.