Abstract: Disclosed subject matter relates to a field of vehicle navigation system that performs a method for determining an optimal trajectory for navigation of an autonomous vehicle. A trajectory determining system associated with the autonomous vehicle may detect an occurrence of a predefined condition related to diversion based on environment data. Further, minimum lateral shift required from a predefined distance for handling the detected predefined condition is determined and co-efficient value sets corresponding to the minimum lateral shift are determined based on pre-stored values that are generated based on a trial run. For each co-efficient value set, velocity and position data is determined at a plurality of time instances based on which one or more trajectories corresponding to each co-efficient value set are generated. Finally, an optimal trajectory is determined among the generated trajectories cumulative variation in orientation and total time required for navigating along the corresponding trajectory.

Abstract: This disclosure relates to method and system for detecting and compensating for mechanical fault in autonomous ground vehicle (AGV). For each of a set of trajectory plan segments along a base path during real-time navigation of the AGV, the method may include receiving a plurality of vehicle displacement parameters along a given trajectory plan segment. and determining an optimal velocity twist of the AGV in the given trajectory plan segment using an artificial intelligence (AI) model, based on the plurality of vehicle displacement parameters and a weight of the AGV. The method may further include determining the mechanical fault in the AGV based on a comparison of an actual velocity twist of the AGV in the given trajectory plan segment and the optimal velocity twist of the AGV in the given trajectory plan segment for each of the set of trajectory plan segments.

Abstract: The disclosure relates to method and system for generating trajectory plan for autonomous ground vehicles (AGV). The method includes assessing an upcoming goal position for an AGV with respect to a current position of the AGV to establish a need for preparing a trajectory plan for a critical segment of the path. The method further includes determining, upon establishing the need, a next free road region based on a hint next rest pose along the critical segment, generating a trajectory sub-plan corresponding to the next free road region by iteratively determining a set of intermediate poses between the current rest pose and the hint next rest pose, and generating the trajectory plan for the critical segment of the path by iteratively generating the trajectory sub-plans between the current rest pose and the final goal pose.

Abstract: This disclosure relates to method and system of generating an enhanced field of view (FoV) for an Autonomous Ground Vehicle (AGV). The method includes determining a set of regions of interest at a current location of an AGV, along a global path of the AGV. Further, for each of the regions of interest, the method includes receiving, for a region of interest, visual data from one or more sensor clusters located externally with respect to the AGV and at different positions. Further, for each of the regions of interest, the method includes for each of the one or more sensor clusters, generating, for a sensor cluster, perception data for the region of interest by correlating the visual data from the two or more vision sensors in the sensor cluster, and combining the one or more entities within the region of interest based on the perception data from the one or more sensor clusters to generate the enhanced FoV.

Abstract: Disclosed herein is a method and system for dynamically generating a secure navigation path for navigation of an autonomous vehicle. The method comprises detecting disproportional acceleration of the autonomous vehicle when the autonomous vehicle is navigating from a source point to a destination point based on a predefined trajectory plan. The method comprises determining direction values of the autonomous vehicle for reaching a secure path point in the predefined trajectory plan. Based on the determined direction values, distance values are determined. The method includes detecting position of the secure path point for navigation of the autonomous vehicle based on the determined direction values and the distance values. The present disclosure uses secure path point to realign the autonomous vehicle in the predefined trajectory plan to overcome the disproportional acceleration of the autonomous vehicle due to narrow roads, upward slope, or downward slope.

Abstract: The disclosure relates to method and system for localizing an autonomous ground vehicle (AGV). In an example, the method includes receiving a line drawing corresponding to a two-dimensional (2D) camera scene captured by a camera mounted on the AGV, determining a plurality of ground-touching corner edges based on a plurality of horizontal edges and a plurality of vertical edges in the line drawing, determining a plurality of three-dimensional (3D) points corresponding to a plurality of 2D points in each of the plurality of ground-touching corner edges based on a mapping relationship between an angular orientation of a ground touching edge of an object in real-world and in camera scene and a set of intrinsic parameters of the camera, generating 2D occupancy data by plotting the plurality of 3D points in a 2D plane, and determining a location of the AGV based on the 2D occupancy data and the mapping relationship.

Abstract: A method and system for determining overtaking trajectory for autonomous vehicles is disclosed. The method includes determining a plurality of dynamic separation distances of an autonomous vehicle from a first vehicle ahead of the autonomous vehicle at predefined time intervals over a period of time. The method further includes generating a trigger for the autonomous vehicle to overtake the first vehicle, when the dynamic separation distance is below a first distance threshold and a current velocity of the autonomous vehicle is greater than a current velocity of the first vehicle. The method further includes determining an overtaking velocity and an overtaking distance for the autonomous vehicle. The method further includes determining an available overtaking region for the autonomous vehicle. The method further includes generating a trajectory for the autonomous vehicle to overtake the first vehicle based on the overtaking distance.

Abstract: Embodiments of the present disclosure relate to generating velocity profiles for an autonomous vehicle (101). An ECU (107) of the autonomous vehicle (101) receives road information from one or more sensors (106) associated with the autonomous vehicle (101). One or more parameters related to smooth movement of the autonomous vehicle on the road is determined from the road information. Further, a first velocity profile is produced using an AI model and a second velocity profile is produced using a hierarchical model, based on the one or more parameters. Furthermore, one of the first and the second velocity profile is selected by comparing the first and the second velocity profiles. The selected velocity profile has a lower value of velocity value compared to the other velocity profile. The selected velocity profile is provided to the autonomous vehicle (101) for navigating on the road (102) smoothly.

Abstract: A method and system for diagnosing autonomous vehicles is disclosed. The method includes identifying anomaly in a set of navigation parameters from a plurality of navigation parameters associated with the autonomous vehicle, such that each of the set of navigation parameters is above an associated risk threshold. The method further includes validating anomaly identified for each of the set of navigation parameters. The method includes generating a set of quality parameters for the set of navigation parameters in response to validating anomaly in the set of navigation parameters. The method further includes generating values of at least one motion parameter associated with the autonomous vehicle based on values of each of the set of quality parameters fed into a trained Artificial Intelligence (AI) model. The method includes controlling the at least one motion parameter based on the generated values.

Abstract: The present invention discloses a method and a system for navigating an Autonomous Ground Vehicle (AGV) using radio signal and vision sensor. The method comprising generating a trajectory plan for a short distance from a path plan, wherein the path plan is determined using destination location and AVG location, identifying an approximate AGV location using a radio signal-based trilateration mechanism, estimating AGV location error with respect to a road lane centre by determining distance from the approximate AGV location to road boundary and road lane marking line and orientation difference between AGV orientation and road orientation, and correcting the trajectory plan by using the estimated AGV location error for navigating an AGV.

Abstract: The present disclosure discloses a method and an Electronic Control Unit (ECU) of autonomous vehicle for validating odometer performance in real-time. The method includes initiating navigation of the autonomous vehicle through a planned path on receipt of a source input and a destination input on a map. A first landmark at a first distance and a first viewing angle and a second landmark at a second distance and second viewing angle is detected from a current position of the autonomous vehicle. A first stored record corresponding to the first landmark based on a first distance match and a second stored record corresponding to the second landmark based on a second distance match is identified. The current position and a next consecutive position of the autonomous vehicle is determined. Reading of the odometer is validated with distance covered by the autonomous vehicle measured between the current position and the consecutive position.

Abstract: This disclosure relates to method and system for detecting and compensating for mechanical fault in autonomous ground vehicle (AGV). For each of a set of trajectory plan segments along a base path during real-time navigation of the AGV, the method may include receiving a plurality of vehicle displacement parameters along a given trajectory plan segment. and determining an optimal velocity twist of the AGV in the given trajectory plan segment using an artificial intelligence (AI) model, based on the plurality of vehicle displacement parameters and a weight of the AGV. The method may further include determining the mechanical fault in the AGV based on a comparison of an actual velocity twist of the AGV in the given trajectory plan segment and the optimal velocity twist of the AGV in the given trajectory plan segment for each of the set of trajectory plan segments.

Abstract: The present disclosure discloses method and an Electronic Control Unit (ECU) (101) of autonomous vehicle for determining an accurate position. The ECU (101) determines centroid coordinate from Global Positioning System (GPS) points, relative to autonomous vehicle and identifies approximate location and orientation of vehicle on pre-generated map based on centroid coordinate and Inertial Measurement Unit (IMU) data. Distance and direction of surrounding static infrastructure is identified from location and orientation of autonomous vehicle based on road boundaries analysis and data associated with objects adjacent to autonomous vehicle. A plurality of lidar reflection reference points are identified within distance and direction of static infrastructure based on heading direction of autonomous vehicle. Position of lidar reflection reference points are detected from iteratively selected shift positions from centroid coordinate.

Abstract: Disclosed herein is method and system for determining correctness of Lidar sensor data used for localizing autonomous vehicle. The system identifies one or more Region of Interests (ROIs) in Field of View (FOV) of Lidar sensors of autonomous vehicle along a navigation path. Each ROI includes one or more objects. Further, for each ROI, system obtains Lidar sensor data comprising one or more reflection points corresponding to the one or more objects. The system forms one or more clusters in each ROI. The system identifies a distance value between, one or more clusters projected on 2D map of environment and corresponding navigation map obstacle points, for each ROI. The system compares distance value between one or more clusters and obstacle points based on which correctness of Lidar sensor data is determined. In this manner, present disclosure provides a mechanism to detect correctness of Lidar sensor data for navigation in real-time.

Abstract: Embodiments of the present disclosure relate to a method and an autonomous navigation system for adaptively navigating an Autonomous Vehicle (AV). The autonomous navigation system obtains a global path comprising a plurality of global waypoints. The global path is generated from a source location to a destination location for the AV to navigate along the global path. A location of the AV is determined where an orientation of the AV deviates from an orientation of the global path. One or more global waypoints are identified, and a global waypoint is selected as reference. Further, proximal to the selected global waypoint, a first set of local waypoints are generated, and a first set of paths are generated from the AV to the first set of local waypoints. A local path is selected based on a cost factor for the AV to navigate along the selected local path.

Abstract: This disclosure relates to method and system for dynamically modifying navigation trajectory of an autonomous ground vehicle (AGV). The method may include receiving an image of a visible road region ahead of the AGV, projecting planned trajectory waypoints on the image, and segmenting the visible road region in the image into equidistant segments along a road length. For each of the equidistant segments, the method may further include determining alternate trajectory waypoints and a suggested velocity for a given segment based on the image of the given segment, a set of the planned trajectory waypoints in the given segment, an adjusted trajectory waypoint in a previous segment, and a determined velocity in the previous segment using an artificial intelligence model. Additionally, for each of the equidistant segments, the method may include determining an adjusted trajectory waypoint based on the alternate trajectory waypoints and the suggested velocity for the given segment.

Abstract: The present invention relates to a method for safely parking an autonomous vehicle on sensor anomaly. Based on current position of the AV, an angular velocity and curvature required for the AV to reach a safe parking space may be determined, upon detecting non-working of at least one primary sensor associated with the AV. Further, one or more obstacles proximal to the AV may be detected using one or more secondary sensors attached to the AV. Furthermore, based on detection of the one or more obstacles, the AV may be navigated in a track by maintaining a safe distance from the one or more obstacles. Finally, the AV may be navigated along the determined curvature upon detecting absence of the one or more obstacles to reach the safe parking space at the edge of the road.

Abstract: Disclosed subject matter relates to vehicle navigation system that performs a method for generating safe navigation path in real-time for safe navigation of vehicle. A path generating system associated with the vehicle may receive a pre-generated navigation path, between source point and destination point. Further, the path generating system may determine uneven points and boundary points on road using sensors configured in the vehicle, within a predetermined volumetric region. Further, a preferred side of the road may be determined and a centre path line may be shifted by a distance towards the preferred side to obtain a new centre path line. Finally, the path generating system may indicate plurality of navigation points on the new centre path line that are curve fitted to generate the safe navigation path for safe navigation of the vehicle. The safe navigation path minimizes jerks experienced by the vehicle and increases safety of vehicle.

Abstract: The present disclosure discloses method and an autonomous navigation system for guiding an autonomous vehicle in forward path in real-time. The method comprises instructing the vehicle to terminate autonomous steering in a forward path, on identifying an angular difference, between a current orientation of the vehicle and orientation of a generated path, to be greater than a predefined threshold value and performing estimation of a frontal area for the vehicle based on a current speed, an orientation, and a width of the vehicle, calculation of a forward turning angle based on the angular difference and a length of the frontal area and guiding vehicle to manoeuvre steer at the forward turning angle within the frontal area, for every predefined time interval, until the angular difference is less than the predefined threshold value. Thus, the present disclosure provides an efficient method for guiding autonomous vehicle in forward path in real-time.

Abstract: The present disclosure relates to generation of a safe navigation path for a vehicle. The safe navigation path is generated by a navigation path generation system. The navigation path generation system receives a reference path from a source location to a destination location. Further, generates scan lines from the reference path to the boundaries present on either side of the reference path. Further, the navigation path generation system generates segment along the boundaries. Further, using the generated segments the navigation path generation system generates a safe navigation path along the centre, between the boundaries present on either side of the reference path. Navigation of the vehicle along the safe path ensures the safety of the vehicle and the people in the vehicle especially when the vehicle is an autonomous or semi-autonomous vehicle.