In the realm of automation, Macro IoT Solution’s Robotics Project stands out as a beacon of innovation. Leveraging advanced technology, they are reshaping industries and pushing the boundaries of what’s possible in robotics.
A Vision-based Collision Avoidance Technique for Micro Air Vehicles Using Local-level Frame Mapping and Path Planning:
This paper presents a vision-based collision avoidance technique for small and Miniature Air Vehicles (MAVs) using local-level frame mapping and path planning. Using computer vision algorithms, a depth map that represents the range and bearing to obstacles is obtained. Based on the depth map, we estimate the range, azimuth to, and height of obstacles using an extended Kalman Filter (EKF) that takes into account the correlations between obstacles.
We then construct maps in the local-level frame using cylindrical coordinates for three-dimensional path planning and plan Dubbin’s paths using the Rapidly-Exploring Random Tree (RRT) algorithm. The behavior of our approach is analyzed and the characteristics of the environments where the local path planning technique guarantees collision-free paths and maneuvers the MAV to a specific goal region are described. Numerical results show the proposed technique is successful in solving path planning and multiple obstacle avoidance problems for fixed wing MAVs.
Project:
- Aeronautics / Avionics / Space Projects,
- Robotics Projects,
- Sensor Projects
A Novel Crowding Genetic Algorithm and Its Applications to Manufacturing Robots:
A niche genetic algorithm (GA) based on a novel twin-space crowding (TC) approach is proposed for solving multimodal manufacturing optimization problems. The proposed TC method is designed in a parameter-free paradigm. That is, when cooperatively exploring solutions with GAs, it does not require prior knowledge related to the solution space to design additional problem-dependent parameters in the evolutionary process.
This feature makes the proposed TC method suitable for assisting GAs in solving real-world engineering optimization problems involving intractable solution landscapes. A set of numerical benchmark functions is used to compare effectiveness and efficiency in the proposed TCGA, in different niche GAs, and in several evolutionary computation methods.
The TCGA is then used to solve multimodal joint-space inverse problems in serial-link robots to compare its convergence performance with that of conventional methods that apply the sharing function. Finally, the TCGA is used to solve iterative collision-free design problems for linkage-bar robotic hands to demonstrate its effectiveness for generating diverse solutions during the design process.
Project:
- IEEE Electronics Projects,
- Robotics Projects
A Climbing Autonomous Robot for Inspection Applications in 3D Complex Environments:
Often inspection and maintenance work involve a large number of highly dangerous manual operations, especially within industrial fields such as shipbuilding and construction. This paper deals with the autonomous climbing robot which uses the “caterpillar” concept to climb in complex 3D metallic-based structures.
During its motion the robot generates in real-time the path and grasp planning in order to ensure stable self-support to avoid the environment obstacles, and to optimize the robot consumption during the inspection. The control and monitoring of the robot is achieved through an advanced Graphical User Interface to allow an effective and user-friendly operation of the robot. The experiments confirm its advantages in executing the inspection operations.
Project:
- Robotics
- Projects
Model-Based Design, Development and Control of an Underwater Vehicle:
With the rising popularity of ROVs and other UV solutions, more robust and high-performance controllers have become a necessity. A model of the ROV or UV can be a valuable tool during control synthesis. The main objective of this thesis was to use a model in design and development of controllers for an ROV. In this thesis, an ROV from Blue Robotics was used.
The ROV boasted 6 thrusters strategically positioned to enable movement in 6 degrees of freedom. Additionally, it featured an IMU, two pressure sensors, and a magnetometer. Further enhancements included EKF-based sensor fusion, a sophisticated control system, and manual control functionalities integrated into the ROV platform. To model the ROV, the framework of Fossen (2011) was used. The model was estimated using two different methods, the prediction-error method and an EKF-based method.
Using the prediction-error method, it was found that the initial states of the quaternions had a large impact on the estimated parameters and the overall fit to validation data. A Kalman smoother was used to estimate the initial states. To circumvent the problems with the initial quaternions, an \abbrEKF was implemented to estimate the model parameters. The EKF estimator was less sensitive to deviations in the initial states and produced a better result than the prediction-error method.
The resulting model was compared to validation data and described the angular velocities well with around 70 % fit. The estimated model was used to implement feedback linearization which was used in conjunction with an attitude controller and an angular velocity controller. Furthermore, a depth controller was developed and tuned without the use of the model. Performance of the controllers was tested both in real tests and simulations.
The angular velocity controller using feedback linearization achieved good reference tracking. However, the attitude controller could not stabilize the system while using feedback linearization. Both controllers’ performance could be improved further by tuning the controllers’ parameters during tests. The fact that the feedback linearization made the ROV unstable, indicates that the attitude model is not good enough for use in feedback linearization.
To achieve stability, the magnitude of the parameters in the feedback linearization were scaled down. The assumption that the ROV’s center of rotation coincides with the placement of the ROV’s center of gravity was presented as a possible source of error. In conclusion, good performance was achieved using the angular velocity controller. The ROV was easier to control with the angular velocity controller engaged compared to controlling it in open loop.
More work is needed with the model to get acceptable performance from the attitude controller. Experiments to estimate the center of rotation and the center of gravity of the ROV may be helpful when further improving the model.
Robotics Project:
- Robotics Projects,
- Sensor Projects
In conclusion with Macro IoT Solution‘s Robotics Project, the future of automation is here. By integrating state-of-the-art technology, they are driving efficiency, productivity, and transformation across various sectors, setting a new standard for robotics excellence.