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What is Graph-based SLAM? Graph-based SLAM is a technique in robotics for creating a map of an environment while simultaneously determining the robot's position within that map. This method uses a graph structure where nodes represent robot poses and landmarks and edges represent spatial constraints between these nodes. Imagine a service robot navigating an office building to deliver documents. The robot needs to build a map of the office while keeping track of its position. Graph-based SLAM helps the robot create a detailed map and accurately estimate its pose as it navigates, ensuring it reaches the correct destinations efficiently. Applications: - Autonomous Robots - Indoor Navigation Systems - Autonomous Vehicles - Drones - Mapping Unknown Environments Techniques: - Pose Graph Optimisation - Loop Closure Detection - Nonlinear Optimisation Methods - Data Association --- akshetpatel.com

The visualization is excellent and enhances comprehension of SLAM technology's application in autonomous navigation systems.

Check out this blog on the impact of NVIDIA in the QSR industry! From delivery drones to autonomous vehicles and robots, learn how advanced technologies are revolutionizing food delivery operations and how the Jetson AGX Xavier is an ideal solution for AI delivery robots.

🆕 Funding opportunity, NOW OPEN 🤖 'Commercial Applications of Space-Enabled Robotics: Smart Cities and Infrastructure'. We invite proposals for feasibility studies and demonstration projects for services that combine satellite technologies and robotics in services or applications for Smart Cities and Infrastructure. ‘Robotics’ could include physical robots, autonomous drones, machines and vehicles, and precursory solutions that enable these (e.g. perception and navigation systems for autonomous vehicle services, connectivity solutions for tele-operated robotic systems). Broader smart city solutions may involve robotics deployed for the purpose of waste collection, street cleaning, autonomous delivery, entertainment, social support, tourism services and beyond. Find full details ➡ https://lnkd.in/em8Dt5S9 #Robotics #RoboticsSolutions #RoboticSystems #RoboticsInnovation #SmartCity #SmartCities #SmartCitySolutions

Here's how robots perceive their environment ❗ Laser scanners and SLAM technology (Simultaneous Localization and Mapping) allow robots to create real-time maps of their surroundings while pinpointing their exact location within those maps. This dual capability ensures precise navigation, enabling autonomous systems like vehicles, drones, and robots to operate safely and efficiently. 🌍✨ P.S. Most autonomous machines today rely on SLAM to function effectively. It's incredible to see how far automation and robotics have advanced! 🤖🚀 Marcin Gwóźdź Lukas M. Ziegler Constantin Weiss Enzo Wälchli Do you want to stay ahead in the world of Supply chain ❗ 🛳️🚚📦 Then Follow Amine BOUDER for the latest updates and industry news. #SLAM #RobotPerception #AutonomousSystems #Innovation #Robotics #Automation

Exploring Multi-Robot Collaboration: A New Frontier in Autonomous Systems Multi-robot collaboration represents a thrilling and evolving domain in the field of autonomous systems, particularly for walking robots. Unlike the more advanced developments seen in ARM (Automated Robotic Machinery) and drone technologies, the realm of autonomous walking robots is still ripe for exploration in areas such as fleet management and swarm behavior. In this innovative space, the potential for robots to work in concert to achieve complex objectives is profound. Imagine scenarios where multiple robots are required to coordinate their movements, share data in real-time, and synchronize their actions to successfully complete tasks that would be impossible for a single unit. These collaborative capabilities can enhance operational efficiency, improve task completion speed, and enable new functionalities that are not feasible with individual robots. Key use cases for multi-robot collaboration include: - Disaster Response: Deploying a fleet of robots to search for survivors, navigate hazardous environments, and perform coordinated rescue operations. - Warehouse Automation: Utilizing multiple robots to manage inventory, transport goods, and optimize warehouse logistics through synchronized efforts. - Environmental Monitoring: Employing a swarm of robots to cover large areas for data collection, environmental analysis, and ecological research, working together to gather comprehensive data efficiently. As we push the boundaries of what autonomous walking robots can achieve through collaborative efforts, we open doors to a host of new possibilities and advancements in robotic technology. #MultiRobotCollaboration #AutonomousSystems #Trendigm #RoboticSwarmBehavior Trendigm | Enabling Innovation

From drones to autonomous vehicles, we're breaking barriers and reshaping the future of mobility. Join our upcoming webinar to gain valuable insights into the intersection of satellite technology and robotics! 🤖 Discover how you can leverage satellite data and space-enabled technologies to transform delivery services, public transportation, and industrial logistics. Don't miss this opportunity to prepare for our upcoming call for proposals and secure funding for your innovative projects. Register now and be part of the future of transportation! 👉https://buff.ly/4arQ2iX #Webinar #Transportation #Logistics #Robotics #Innovation #SpaceTechnology 🌐🚚🛰️

🚗 AI is driving us towards an autonomous future, but are we truly prepared for the ethical challenges it brings? Self-driving cars, drones, and robots will soon play a big role in our lives—how do we ensure they make the right decisions? What’s your stance on AI ethics in autonomous systems? #AIEthics #AutonomousTech #ArtificialIntelligence #EthicalAI

How are manufacturers using autonomous machines, mobile robots, and drones to speed up production and cut costs? Register to hear experts from Hitachi, Slalom, and Cyper Robotics explore how #Private5G is transforming #SmartFactories.

AI in autonomous systems enhances efficiency, safety, and functionality across various applications. In self-driving cars, AI enables real-time navigation, obstacle detection, and decision-making. Drones use AI for precise navigation and delivery. Industrial robots employ AI for tasks like assembly and quality control, reducing human error and increasing productivity. #AI #AutonomousSystems #ArtificialIntelligence https://lnkd.in/gyw2ugMa