Optimal Path Planning of Autonomous Robots
With the advent of autonomous systems and their applications in domestic and industrial work, Robot path planning has become an important research domain. Robots are used for household activities, hospital assistance, agricultural work, and autonomous cars to name a few. With the current pandemic si
2025-06-28 16:28:44 - Adil Khan
Optimal Path Planning of Autonomous Robots
Project Area of Specialization RoboticsProject SummaryWith the advent of autonomous systems and their applications in domestic and industrial work, Robot path planning has become an important research domain. Robots are used for household activities, hospital assistance, agricultural work, and autonomous cars to name a few. With the current pandemic situation and the pressure at the current medical backbone structure, the need for hospital assistive robot has become evident. Path planning is done to determine the path which is most efficient considering the environment and its obstacles. Autonomous robotic path planning is an active area of research due to its domestic applications. The main challenges include: Time efficient and shortest path, non-redundant path points, cost efficient path, robot trap avoidance. The overall view of this project is to study, test, and compare numerous paths planning algorithms and propose an efficient algorithm to cater the aforementioned issues for an efficient hospital assistive robot path. An optimal path is the path that originates from source to destination while ensuring that the challenges faced are minimized. Many researchers have proposed numerous algorithms for optimizing techniques. However, our main area of focus is to study the characteristics and purpose of algorithms of different domain and come up with a hybrid approach of Evolutionary and Grid based algorithms to fulfill our requirements.
Project ObjectivesKeeping in view the current load on medical personals during the ongoing pandemic, the main objective of this project is to propose an efficient collision free path planning algorithm with minimum energy and memory requirements for hospital assistive robots. The proposed algorithm will be implemented on 2D known environment with dynamic obstacles to mimic the busy hospital workspace. Different types of algorithms will be researched, analyzed and hybrid algorithm will be produced to not be bound of limitations of a single algorithm and all the requirements can be fulfilled. The algorithms will be tested in MATLAB simulations with real world map and later testing will be done in real world environment.
Project Implementation MethodThe project will be implemented using the following technologies:
- The environment map will be captured using camera and fed in simulation environment as a reference. This initial map will be used as a base line for the run time programming and assessment of algorithm.
- The dynamic obstacles and the real-world environment configurations will be sensed by using infrared sensor. And the map will be updated accordingly.
- ROS will be used to integrate the navigation libraries and basic functionalities of robot
- The configuration model of the code bot will be integrated with ROS.
The project is divided into two phases. The first phase is proposing an efficient algorithm for path planning of hospital assistive robots and extensively testing the proposed algorithm in a simulation-based environment. The second phase comprises of testing the proposed algorithm in real world environment. There are few considerations to keep in view
- The environment is closed.
- The sensors are working and the input is correct
- The offset distance is maintained
- The source and destination points lie in the free space
As the robots are being widely used nowadays, it is crucial to increase the efficiency of their movement from a source to destination. Our project will devise a hybrid algorithm which will provide a path i.e.:
- Shortest Collision free to ensure human safety in busy and cluttered environments of hospitals
- Free of redundant points
- Free of getting trapped in any region
- Time and memory efficient algorithm
The final deliverable will be consisting of the following modules:
- An interactive module for the user to mark the starting point and the destination for the CODEBOT.
- A hybrid algorithm implemented on MATLAB/ROS interface and tested on CODEBOTS in a real-world environment.
- Test case results tested on a personal computer with Intel Core i5 CPU, 8GB RAM, and Intel HD Graphics 620.
- The final deployment on CODEBOT to validate the working for hospital assistive robots
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 36200 | |||
| CODEBOT | Equipment | 1 | 29000 | 29000 |
| Infrared sensor | Equipment | 2 | 500 | 1000 |
| Distance Sensor | Equipment | 2 | 600 | 1200 |
| TF-Luna distance Sensor | Equipment | 1 | 5000 | 5000 |