Abstract: An embodiment herein provides a re-configurable unmanned aerial vehicle that re-configures its shape based on the shape, size, weight of a payload, and efficiently performs payload delivery in real-time. The re-configurable unmanned aerial vehicle includes one or more rotor units placed at corners and is connected by one or more scissor units. The re-configurable unmanned aerial vehicle approaches the payload in a first location, and analyses the position and dimension of the payload with a camera, that enables the one or more scissor units to adjust its length by at least one elongation or compression following size and shape of the payload and fit the payload within the re-configurable unmanned aerial vehicle. The re-configurable unmanned aerial vehicle takes off carrying the payload from the first location and lands at a second location.

Abstract: The present disclosure provides a model for semantic navigation for service robots to find out-of-view objects in an indoor environment. Initially, the system receives a target object to be reached by the mobile robot in the indoor environment. Further, a current location of the mobile robot is identified by a localization technique. An embedding corresponding to each of a plurality of visible regions is computed using a pretrained Graph Neural Network GNN. The GNN is pretrained using a trajectory data and a spatial relationship graph associated with the indoor environment. Further, a similarity score is computed for each of the plurality of visible regions based on the corresponding embedding using a scoring technique. An optimal visible region is identified by comparing the similarity score. Finally, a next action to be taken by the mobile robot selected from a plurality of actions based on the optimal visible region.

Abstract: The embodiments herein provide a system and method for integrating objects in monocular simultaneous localization and mapping (SLAM). State of art object SLAM approach use two popular threads. In first, instance specific models are assumed to be known a priori. In second, a general model for an object such as ellipsoids and cuboids is used. However, these generic models just give the label of the object category and do not give much information about the object pose in the map. The method and system disclosed provide a SLAM framework on a real monocular sequence wherein joint optimization is performed on object localization and edges using category level shape priors and bundle adjustment. The method provides a better visualization incorporating object representations in the scene along with the 3D structure of the base SLAM system, which makes it useful for augmented reality (AR) applications.

Abstract: In state of the art methods for object goal navigation, scene understanding is implicit in their goal oriented exploration policies. Implicit scene understanding coupled with navigation is shown to be specific to tasks for which training is done and not generalizable to new tasks. Thus, embodiments of present disclosure propose a method of goal-conditioned exploration wherein scene understanding is decoupled from the exploration policies. Here, the scene understanding required for navigation is provided by a region classification network that is trained using semantic graphs representing the scene and agent can be navigated towards the goal either by using any state of the art pure exploration policies or by traversing through potential sub-goals identified based on a Co-occurrence Likelihood score calculated by using predictions from the region classification network. Hence, the method of present disclosure can be easily generalized to new tasks and new environments.

Abstract: The disclosure herein generally relates to the field of autonomous navigation, and, more particularly, to a diverse trajectory proposal for autonomous navigation. The embodiment discloses a hierarchical network based diverse trajectory proposal for autonomous navigation. The hierarchical 2-stage neural network architecture maps the perceived surroundings to diverse trajectories in the form of trajectory waypoints, that an autonomous navigation system can choose to navigate/traverse. The first stage of the disclosed hierarchical 2-stage Neural Network architecture is a Trajectory Proposal Network which generates a set of diverse traversable regions in an environment which can be occupied by the autonomous navigation system in the future. The second stage is a Trajectory Sampling network which predicts a fine-grained trajectory/trajectory waypoint over the diverse traversable regions proposed by Trajectory Proposal Network.

Abstract: A telescopic differential screw mechanism based 3-DOF Parallel Manipulator system to enable differential length and omnidirectional bending is provided. The telescopic differential screw mechanism based 3-DOF Parallel Manipulator system includes a first circular rotating plate 102, a second circular rotating plate 104, three or more telescopic screw assemblies 106A-C and three or more actuators 108A-C. Each telescopic screw assembly 106 includes a pair of master screws 110, a pair of successive screws 112 and a universal joint 116. The three or more telescopic screw assemblies 106A-C are actuated differentially using the three or more actuators 108A-C to achieve omnidirectional bending with high angular rotations in a range of 0 to 75 degree.

Abstract: The embodiments herein provide a system and method for integrating objects in monocular simultaneous localization and mapping (SLAM). State of art object SLAM approach use two popular threads. In first, instance specific models are assumed to be known a priori. In second, a general model for an object such as ellipsoids and cuboids is used. However, these generic models just give the label of the object category and do not give much information about the object pose in the map. The method and system disclosed provide a SLAM framework on a real monocular sequence wherein joint optimization is performed on object localization and edges using category level shape priors and bundle adjustment. The method provides a better visualization incorporating object representations in the scene along with the 3D structure of the base SLAM system, which makes it useful for augmented reality (AR) applications.

Abstract: The disclosure herein generally relates to the field of autonomous navigation, and, more particularly, to a diverse trajectory proposal for autonomous navigation. The embodiment discloses a hierarchical network based diverse trajectory proposal for autonomous navigation. The hierarchical 2-stage neural network architecture maps the perceived surroundings to diverse trajectories in the form of trajectory waypoints, that an autonomous navigation system can choose to navigate/traverse. The first stage of the disclosed hierarchical 2-stage Neural Network architecture is a Trajectory Proposal Network which generates a set of diverse traversable regions in an environment which can be occupied by the autonomous navigation system in the future. The second stage is a Trajectory Sampling network which predicts a fine-grained trajectory/trajectory waypoint over the diverse traversable regions proposed by Trajectory Proposal Network.

Abstract: A multidirectional locomotive module with omnidirectional bending that is compliant along multiple axis is provided. The locomotive module includes, (A) a first part that includes (i) one or more circular rigid components which are coupled using a two degree of freedom joint, (ii) bending actuator that actuates the two degree of freedom joint enabling bending of the multidirectional locomotive module to an angle ranging from 0 to 90 degrees about a Z-axis in a direction to achieve surface compliance with an external surface, and (B) a second part that is elongated in shape with circular cross-section along a surface length and hemispherical in shape an end portion with a surface that is formed by a power transmission sprocket chain and an arrangement of curved components enabling sideways rolling of the multidirectional locomotive module, also enabling wheeled and legged locomotion in vertical position.

Abstract: A multidirectional locomotive module with omnidirectional bending that is compliant along multiple axis is provided.

Abstract: A telescopic differential screw mechanism based 3-DOF Parallel Manipulator system to enable differential length and omnidirectional bending is provided. The telescopic differential screw mechanism based 3-DOF Parallel Manipulator system includes a first circular rotating plate 102, a second circular rotating plate 104, three or more telescopic screw assemblies 106A-C and three or more actuators 108A-C. Each telescopic screw assembly 106 includes a pair of master screws 110, a pair of successive screws 112 and a universal joint 116. The three or more telescopic screw assemblies 106A-C are actuated differentially using the three or more actuators 108A-C to achieve omnidirectional bending with high angular rotations in a range of 0 to 75 degree.