Tata Consultancy Services Limited

Arnab Sinha

Ranjan Dasgupta

Mohit Ludhiyani

Vishvendra Rustagi

Arup Kumar Sadhu

Titas Bera

Bharat Kumar Thakur

This disclosure relates generally to real-time path planning. Planning amidst obstacles in a cluttered indoor environment is a difficult task for a robotic agent. The disclosed method provides semidefinite programming induced free-space based path planning. Free-space is generated by an efficient environment grid resolution independent seeding technique. In the proposed resolution independent seeding technique, initial position of the robotic agent is considered as the first seed. For subsequent seeding, information of the expanded earlier seeds are employed intelligently. This process is followed unto a finite sequence, which naturally results in a contiguous navigable convex free-space. This contiguous navigable convex free-space is employed to create an undirected graph, which is then used for path planning. Path planning is done locally by evaluating the subgoal with respect to a final goal. Local planning cumulatively assists the planner to attain the final goal.

Method and system for real-time path planning

Embodiments of the present disclosure provide systems and methods to eliminate (or filter) drift for dynamics model based localization of multirotors. The dynamics equations require drag modelling, which is dependent on velocity, to generate vehicles' acceleration along the body axis. The present disclosure considers the drag contribution, at velocity level, as a low frequency component. Incorrect or nonmodelling of this low frequency component leads to drift at velocity level. This drift can then be removed through a high pass filter to obtain drift free velocity data for pose estimation and better localization thereof.

Drift-free velocity estimation for multirotor systems and localization thereof

State of art systems in the domain of dynamism detection fail to estimate noise if depth images are being collected as input for the dynamism detection, as the noise in depth images depend on the scene being captured. Disclosed herein are method and system for determining dynamism by processing depth image of a scene. The system models depth sensor noise as ergodic stochastic process by determining that distribution estimated at each reference pixel from a plurality of neighborhood pixels in a reference image being processed is statistically same as a distribution estimated from evolution of the reference pixel over the time. After modeling the depth sensor noise in this manner, the same is eliminated/removed from the reference image, which is then processed to estimate divergence at each pixel based on temporal and spatial distribution built at pixel level in the reference image, and in turn determines dynamism in the scene.

Method and system for determining dynamism in a scene by processing depth image

Robotic vision-based framework wherein an on-board camera device is used for scale estimation. Unlike conventional scale estimation methods that require inputs from more than one or more sensors, implementations include a system and method to estimate scale online solely, without any other sensor, for monocular SLAM by using multirotor dynamics model in an extended Kalman filter framework. This approach improves over convention scale estimation methods which require information from some other sensors or knowledge of physical dimension of an object within the camera view. An arbitrary scaled position and an Euler angle of a multirotor are estimated from vision SLAM (simultaneous localization and mapping) technique. Further, dynamically integrating, computed acceleration to estimate a metric position. A scale factor and a parameter associated with the multirotor dynamics model is obtained by comparing the estimated metric position with the estimated arbitrary position.

System and method of multirotor dynamics based online scale estimation for monocular vision

An XML template having one or more nodes is received. Mapping information indicating an association of data and nodes of the uploaded XML template is obtained. Once the mapping is received, the structure of the XML template is determined. Based on the determined structure and the mapping provided, an XML based SQL query is generated. The generated SQL query can be executed to provide the XML document.

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Kolkata, India

Arnab Sinha