Tata Consultancy Services Limited

Tata Conulstancy Services Limited

Ashis Sau

Abhijan Bhattacharyya

Madhurima Ganguly

Balamuralidhar Purushothaman

Brojeshwar Bhowmick

Arpan Pal

Chayan Sarkar

Ruddra Dev Roychoudhury

Snehasis Banerjee

Pradip Pramanick

Hrishav Bakul Barua

Sayan Paul

Suraj Kumar Mahato

Sanjana Sinha

Sandika Biswas

Dipanjan Das

Soumyadip Maity

Kritika Anand

Ruddra Roy Chowdhury

State of the art data transmission approaches require all the lost data packets to be retransmitted, which may not be required in a variety of scenarios. Existing protocols lack the option to change packet semantics on the fly for individual fragments on the fly for the same stream. Also, parameters including maximum number of retransmissions permitted are set beforehand, one for entire stream. Method and system in embodiments disclosed herein provide an approach for context-based retransmission of lost packets. Method and system disclosed in the embodiments herein identifies one or more packets as lost packets based on reception status of acknowledgement (ACK) within a dynamically adaptive timeout period, and then based on value of a NRTx header field associated with the lost packet, determines whether or not to retransmit the lost packet. Value of the dynamically adaptive timeout period is recalculated dynamically, based on a determined instantaneous channel condition.

Method and system for context-based retransmission of lost packets

This disclosure provides a Kalman filter based predictive jitter buffer adaptation for smooth live video streaming. In the present disclosure, at receiver of a live video steaming system, reassembly of received data packets is performed to reconstruct different types of encoded frames transmitted by a transmitter. The different types of encoded frames are Full encoded frames in basic state and Delta encoded frames. To tackle data packet loss, the receiver is also equipped with a frugal yet efficient loss handling mechanism for both basic and delta frames. To achieve smooth rendering of the live video, the receiver employs a Kalman Filter based Jitter Buffer Adaptation mechanism. The Kalman Filter based Jitter Buffer Adaptation mechanism observes variability in arrival time of the open-loop best-effort traffic and adapts a jitter-buffer based on future end-to-end delay estimates. Thus, smoothness of streaming is preserved at the receiving end augmented with robust loss-resilience.

Kalman filter based predictive jitter buffer adaptation for smooth live video streaming

Telerobotic systems that are available currently for enterprise uses are mostly cloud centric systems i.e., they require Internet connection for functioning. Too much cloud-centricity not only increases overall latency in getting decision outcome, but also adds a certain probability of uncertainty in performance and availability of the cloud-service due to unreliability in the public Internet backhaul. Present disclosure provides method and system for managing telerobotic session in enterprise network. The system first identifies dew signaling server for communication wherein a telerobotic device present in enterprise network offer to act as dew signaling server. The system then establishes a peer-to-peer (P2P) connection between dew signaling server and a cloud signaling server present in a public cloud for instantiating the dew signaling server. Thereafter, when system receives the enterprise level signaling requests from enterprise user devices, the system redirects enterprise level signaling requests to dew signaling server using enterprise network proxy.

Method and system for managing telerobotic session in an enterprise network

Currently available live media distribution systems have to continuously maintain multiple peer-to-peer (P2P) connections which further increases the computational load of robot. Present disclosure provides a method and a system for managing multimedia exchange in tele-robotics using dew computing. The system first identifies a dew signaling server wherein a tele-presence robot device present in enterprise network offer to act as dew signaling server. The system then establishes first P2P connection between dew interface and dew signaling server. Thereafter, system establishes second P2P connection between dew signaling server and cloud media manager present in public cloud server. Further, system identifies computing device present in enterprise network as dew media manager. The system then establishes third P2P connection between dew media manager and the cloud media manager via the cloud signaling server. The dew media manager then perform multimedia exchange within one or more enterprise user devices connected to enterprise network.

Method and system for managing multimedia exchange in tele-robotics using dew computing

The disclosure relates generally to methods and systems for quality of experience (QoE)-centric adaptive bitrate encoding for a live video stream. Conventional QoE aware Adaptive Bit Rate (ABR) scheme may not be suitable for live interactive streams especially in bandwidth limited practical situations and does not address the core issues inherent in present ABR schemes. The present models the adaptation as a context specific multi-model tuning mechanism and provides a dual adaptation control for spatial encoding of each frame. This involves defining a starting region of potential attention by the user based on a standard estimate of eye-foveation with respect to the field of view (FOV) and then adapting it through a foveal-breathing technique. Further, a median based sparsification of quantized DCT coefficient matrix for each minimum coded unit (MCU) of a frame is introduced to satisfy channel bit budget without compromising the quality of the foveal region.

Methods and systems for quality of experience-centric adaptive bitrate encoding for live video streaming

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

The present disclosure addresses an issue of inherent delay in a cloud-centric architecture in a scenario where multiple remote users join a teleoperation session with a robot such that any one of the users may take exclusive control of the robot and remotely maneuver it as the avatar of a current master. A Web Real-Time Communication (WebRTC) based signaling protocol with a hybrid topology for a multi-user session is provided, wherein Audio-Visual (A/V) data streaming happens over a public cloud while each master creates an on-demand peer-to-peer (P2P) channel with the robot for a desired duration of maneuvering the robot that represents the avatar of the current master. Thus, low-latency delivery of control commands results in good user experience. The provided method and system may be applied to teleoperation sessions like telemedicine sessions.

Multi-master hybrid telerobotics system with federated avatar control

This disclosure relates generally to navigation of a tele-robot in dynamic environment using in-situ intelligence. Tele-robotics is the area of robotics concerned with the control of robots (tele-robots) in a remote environment from a distance. In reality the remote environment where the tele robot navigates may be dynamic in nature with unpredictable movements, making the navigation extremely challenging. The disclosure proposes an in-situ intelligent navigation of a tele-robot in a dynamic environment. The disclosed in-situ intelligence enables the tele-robot to understand the dynamic environment by identification and estimation of future location of objects based on a generating/training a motion model. Further the disclosed techniques also enable communication between a master and the tele-robot (whenever necessary) based on an application layer communication semantic.

Navigation of tele-robot in dynamic environment using in-situ intelligence

This disclosure relates generally to method and system for live video streaming with integrated encoding and transmission semantics. The system receives a set of frames associated with a live video stream encoded to generate a set of data fragments using a reference encoder and a delta encoder. Transmitter unit of the live video streaming protocol transmits each packet of the set of full frames and the set of delta frames in sequence with a payload specific header based on a packet mode. Further, the receiver unit receives each packet of the full frames and each packet of the delta frames based on the packet mode to reconstruct an original sequence from the foreground pixels by estimating a total number of packets expected at each frame interval and loss incurred in each packet of the set of full frames and the set of delta frames.

Method and system for live video streaming with integrated encoding and transmission semantics

Conventional tele-presence robots have their own limitations with respect to task execution, information processing and management. Embodiments of the present disclosure provide a tele-presence robot (TPR) that communicates with a master device associated with a user via an edge device for task execution wherein control command from the master device is parsed for determining instructions set and task type for execution. Based on this determination, the TPR queries for information across storage devices until a response is obtained enough to execute task. The task upon execution is validated with the master device and user. Knowledge acquired, during querying, task execution and validation of the executed task, is dynamically partitioned by the TPR across storage devices namely, on-board memory of the tele-present robot, an edge device, a cloud and a web interface respectively depending upon the task type, operating environment of the tele-presence robot, and other performance affecting parameters.

Knowledge partitioning for task execution by conversational tele-presence robots in a geographically separated environment

Robotic platform for tele-presence applications has gained paramount importance, such as for remote meetings, group discussions, and the like and has sought much attention. There exist some robotic platforms for such tele-presence applications, these lack efficacy in communication and interaction between remote person and avatar robot deployed in another geographic location thus adding network overhead. Embodiments of the present disclosure for edge centric communication protocol for remotely maneuvering tele-presence robot in geographically distributed environment. More specifically, edge-centric tele-presence robot architecture is provided for maneuvering tele-presence robot in distributed geographical environment, wherein the architecture provides a framework that implements both cloud and edge-centric systems together with a first communication protocol for communication between a master device and an edge device and a second communication protocol different from the first communication protocol for communication between the edge device and the tele-presence robot to improve robustness and efficacy in communication.

Edge centric communication protocol for remotely maneuvering a tele-presence robot in a geographically distributed environment

This disclosure relates generally to method and system for enhancing Quality of experience (QoE) for rendering live interactive videos in real-time. The conventional methods utilize an additional field in packet header to determine which packet sequences were lost, so that the receiver could request a retransmission. Due to unpredictable delay and loss, the receiver may not get the end-of-frame packet which has been sent using best-effort. The disclosed method and system introduced an additional indicator to identify an expected maximum number of packets transmitted for each frame, and further determine the distribution of loss so that the rendering unit can intelligently decide on whether to allow the frame to display, or to drop it without using any additional retransmission or error-concealment strategy, thereby enhancing the QoE of reception at the receiver.

Method and system for enhancing quality of experience (QOE) of video reception at receiver

The disclosure generally relates to methods and systems for maintaining quality of experience (QoE) in real-time live video streaming. Conventional techniques in achieving the QoE employ either additional bandwidth of the network or compromise on a latency of the network. The present disclosure provides a rendering algorithm to compensate for lost entropy without attempting to regain exact lost packet(s) information. The rendering algorithm enhance the QoE by regaining structural continuity of the lost packet(s) information despite variations in the end-to-end transmission channel. A segmentation algorithm is employed to segment each frame into one or more packets, so that each packet should only have integer number of MCU blocks. The rendering algorithm to identify the lost packets and to compensate the lost information. The present disclosure provides a loss resilient solution to maintain the QoE without trading off the bandwidth efficiency and the network latency.

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Kolkata, India

Ashis Sau