Tata Consultancy Services Limited

Kritika Anand

Brojeshwar Bhowmick

Snehasis Banerjee

Abhijan Bhattacharyya

Chayan Sarkar

Ashis Sau

Pradip Pramanick

Ravindra Naik

Ruddra Dev Roychoudhury

Pavan Kumar Chittimalli

Gulshan Kumar

Sai Shankar Narasimhan

Madhava Krishna Krishnan

A model for semantic navigation for service robots to find out-of-view objects in an indoor environment is provided. 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.

Method and system for semantic navigation using spatial graph and trajectory history

The embodiments of present disclosure herein address unresolved problem of cognitive navigation strategies for a telepresence robotic system. This includes giving instruction remotely over network to go to a point in an indoor space, to go an area, to go to an object. Also, human robot interaction to give and understand interaction is not integrated in a common telepresence framework. The embodiments herein provide a telepresence robotic system empowered with a smart navigation which is based on in situ intelligent visual semantic mapping of the live scene captured by a robot. It further presents an edge-centric software architecture of a teledrive comprising a speech recognition based HRI, a navigation module and a real-time WebRTC based communication framework that holds the entire telepresence robotic system together. Additionally, the disclosure provides a robot independent API calls via device driver ROS, making the offering hardware independent and capable of running in any robot.

Telepresence robots having cognitive navigation capability

This disclosure relates generally to detection of inconsistencies in Semantics of Business Vocabulary and Business Rules (SBVR) rules, and, more particularly, to detecting inconsistencies in SBVR using Many-Sorted Logic. Traditional systems and methods implementing graphical and other related techniques are not sufficient to detect anomalies in semantic rules, thereby leading to a different verification approach to detect logical anomalies and errors due to quantification. Embodiment of the present disclosure overcome the limitations faced by the traditional systems and methods by translating a set of SBVR rules into a SBVR eXtensible Markup Language Metadata Interchange (XMI); transforming the SBVR XMI into one or more Satisfiability Modulo Theories Library (SMT-LIB) formulas using at least one logical structure and semantic of Many-Sorted Logic; and detecting, from the one or more SMT-LIB formulas, one or more inconsistencies in semantics of SBVR by using a SMT solver invocation.

Detecting inconsistencies in semantics of business vocabulary and business rules (SBVR) using many-sorted logic

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Pune, India

Kritika Anand