Abstract: The disclosure provides a method and system for multi-robot route planning. The method includes determining a route plan of a node based on an order value associated with the node, wherein the order value is distance travelled from the node to one or more nodes in a network, occupying an order slot from a list of orders of the node. The determined route plan of the node is sent to the one or more nodes in the network and a new route plan is generated, based on order value threshold and wait time estimate associated with the node. The method includes optimizing the generated new route plan of the node comprising computing a new order value occupying a new order slot from the list of orders of the node in parallel to change in status of order value of the one or more nodes.

Abstract: A system and a method to optimize route plans for handling critical scenarios faced in an operating environment have been described. The system or a platform resolves one or more nodes based on the inputs related to an operating environment. The system plans one or more routes based on the resolved nodes to provide generated route plans. Based on the planning, the system may analyze one or more route plans for critical scenarios, for example, avoiding a collision or minimizing congestion, damage to the robot, performance of vehicle or warehouse, etc. After the route plans are analyzed, the system optimizes one or more route plans to provide optimized route plans. The optimized route plans are distributed to one or more autonomous vehicles. The fleet of autonomous vehicles may then route progress messages and share feedback with the platform.

Abstract: The disclosure generally relates to method and system for autonomous vehicles management in an operating environment. The method may include sending a route plan in response to a request received by an autonomous vehicle from amongst a plurality of autonomous vehicles in an operating environment including one or more devices, wherein the one or more device comprises device or device space. The method may further include categorizing the route plan into path segments, the path segments including a first path segment including one or more nodes from the plurality of nodes being inside a device zone of the one or more devices and a second path segment including one or more nodes from the plurality of nodes being outside the device zone of the one or more devices.

Abstract: The disclosure relates to method and system for geographic routing mesh network. The method may include determining, by a first node, a first list of nodes proximal to the first node in a mesh network. The method further includes sending, by the first node to each node on the first list of nodes, the first list of nodes proximal to the first node. The method(s) further includes receiving, by the first node in response to sending the first list of nodes, one or more second list of nodes from one or more nodes of the first list of nodes, each of the one or more second list of nodes being proximal to one of the one or more nodes of the first list of nodes and updating, by the first node in response to receiving one or more second list of nodes proximal to the one more nodes of the first list of nodes, one or more nodes of the first list of nodes.

Abstract: Embodiments herein disclose methods and systems to avoid congestion in an area by a plurality of robots awaiting access to a common resource. A current robot action and a sensor data of one of the plurality of robots is received at a cloud node. Based on the received current robot action and the sensor data, a determination is made whether the one of the plurality of robots has to access the common resource. Next, a spatial query is executed at the cloud node to determine a location in the area for positioning the one of the plurality of robots awaiting access to the common resource based on a static spatial condition that requires a congestion-free movement when the robot is positioned at the location in the area. Next, based on a collaboratively determined priority order, the common resource is accessed by the one of the plurality of robots.

Abstract: Embodiments herein disclose methods and systems for generating a 2D-navigation map for collision-free navigation by a plurality of robots. Initially, a 2D-navigation map generator executing at a cloud map server initiates a particle simulation to add a plurality of bubbles to an image of an area. Next, the 2D-navigation map generator executing at the cloud map server, processes the bubble simulation to determine a set of bubbles from the plurality of robots on the image that are overlapping free spaces of the area in the image. Next, the 2D-navigation map generator executing at the cloud map server, generates the 2D-navigation map by connecting the set of bubbles using a plurality of edges, wherein the plurality of edges indicate a navigation path to navigate within the area. Finally, based on the generated 2D-navigation map, the plurality of robots traverses from a current location to another location.

Abstract: A system and method to generate and deploy a cloud device application has been described. Initially a software service is selected from a software service store to generate the cloud device application. A selection of composition pattern is then received for generating a cloud device application including the software service. Based on the composition pattern an instance of the software service is generated and deployed at cloud and one or more devices. Next an instance of the application is generated and bound to the deployed instance of the software service. Finally the instance of the application bound to the deployed instance of the software service is deployed to the cloud and the one or more devices.

Abstract: A system and method to build and deploy a cloud device application a cloud and a plurality of devices has been described. Initially a selection of software executable code and runtime architecture of one of the cloud and the plurality of devices is received for deploying the cloud device application including the software executable code. Next a builder image is selected for generating a software executable image corresponding to the software executable code. Next a build process is executed to generate the software executable image corresponding to the software executable code based on the selected builder process. Finally the generated software executable image on one of the cloud and one of the plurality of devices is deployed based on the runtime architecture.

Abstract: Embodiments herein disclose methods and systems to generate, simulate, and execute a reusable robotic solution recipe for executing a robotic solution. Initially a selection of one or more hardware components to be included in the reusable robotic solution recipe is received at a web user interface. Next a selection of a software component is received from the displayed one more software components to be included in the reusable robotic solution recipe. Next the hardware-vendor agnostic controller executes the reusable robotic solution recipe to determine hardware and environment component configuration for executing the robotic solution. A model descriptor file is invoked to determine defined hardware and environment data configuration. Based on the determined and the defined hardware and environment component configuration execution of the robotic solution is initiated.