Tata Consultancy Services Limited

Aniruddha Singhal

Rajesh Kumar Sinha

Venkatesh Prasad Bangalore Srinivas

Venkat Raju Chintalapalli Patta

Ankush Ojha

Supratim Ghosh

Chayan Sarkar

Marichi Agarwal

Harshad Khadilkar

Laxmidhar Behera

Aditya Jain

Venkatesh Srinivas Prasad

Deepak Raina

Venkat Raju Chinatalapalli Patta

Richa Verma

Shivam Thukral

Vipul Ashok Sanap

A fully automated and reliable picking of a diverse range of unseen objects in clutter is a challenging problem. The present disclosure provides an optimum grasp pose selection to pick an object from a bin. Initially, the system receives an input image pertaining to a surface. Further, a plurality of sampled grasp poses are generated in a random configuration. Further, a depth difference value is computed for each of a plurality of pixels corresponding to each of the plurality of sampled grasp poses. Further, a binary map is generated for each of the plurality of sampled grasp poses and a plurality of subregions are obtained. Further, a plurality of feasible grasp poses are selected based on the plurality of subregions and a plurality of conditions. Further, the plurality of feasible grasp poses are refined and an optimum grasp pose is obtained based on a Grasp Quality Score (GQS).

Method and system for point cloud based grasp planning framework

Online 3-dimensional bin packing problem (O3D-BPP) is getting renewed prominence due to the industrial automation brought by Industry 4.0. However, due to limited attention in the past and its challenging nature, a good approximate technique is in scarcity as compared to 1D or 2D problems. Present disclosure provides system and method that considers real-time O3D-BPP of cuboidal boxes with partial information (look-ahead) in an automated robotic sorting center. System presents two rolling-horizon mixed-integer linear programming (MILP) cum-heuristic based algorithms wherein a framework is provided that adapts and improves performance of BP heuristics by utilizing information in an online setting with look-ahead.

Automated placement of objects in bins using look ahead information by virtual sorting and packing

State of the art automated bin packing systems fail to handle dynamic scenarios in which information on dimensions of objects to be loaded is not available in advance. These systems also fail to consider capabilities of robots used for the automated packing of objects/bins. The disclosure herein generally relates to automated bin packing, and, more particularly, to a system and method for autonomous multi-bin parcel loading system. The system handles an online object packing in which information on dimensions of objects to be loaded is not available in advance. The system is also configured to consider capabilities of one or more robots used for loading objects to containers, while generating recommendations for object packing.

System and method for autonomous multi-bin parcel loading system

This disclosure relates generally to automated packing of objects, and, more particularly, to a method and system for packing products with increased efficiency across packaging levels. While conventional methods of improving packaging efficiency focus on only one of the multiple levels in the packaging process, most commonly the tertiary level, the present disclosure attempts increasing packaging efficiency across packaging levels. Embodiments of present disclosure achieves increased efficiency across packaging levels by identifying standard size of secondary packages for packing a plurality of primary packages, packing the secondary packages within tertiary packages using a Mixed Integer Linear Programming (MILP) optimization model based on packing heuristics, and providing a feedback between tertiary and secondary packaging levels to identify standard secondary packages which can pack the primary packages with higher packing efficiency.

Method and system for packing products with increased efficiency across packaging levels

Embodiments herein provide automated bin packing of heterogeneous objects to fill maximum number of objects in an available bin space in an efficient manner. Conventional methods are less efficient in packing heterogeneous objects in a space and time efficient manner. The apparatus receives a plurality of 3D objects through a primary conveyor and diverts each of the plurality of 3D objects to an identified cuboidal bin through a corresponding secondary conveyor. Each of the plurality of 3D objects are diverted based on a tracking code associated with each of the plurality of 3D objects and a computed available bin space of the identified cuboidal bin corresponding to each of the plurality of 3D objects. Here the available bin space is computed based on a bin space information received from a corresponding bin vision sensor and a corresponding state space of the identified cuboidal bin.

Apparatus and method for packing heterogeneous objects

This disclosure relates generally to a robotic gripper to hold a writing and object creation device for writing and object creation. The robotic gripper includes clamping unit, spring loaded slider unit and outer housing unit. The clamping unit include a finger collet with three or more flexible finger positions equispaced within 360 degrees with two areas of contact on each finger in front part for firm gripping. The spring loaded slider unit include a middle housing to transfer a force from the writing and object creation device to a force sensitive resistor (FSR). A micro actuator induces a required force to the writing and object creation device based on feedback from the force sensitive resistor. The middle housing includes a plunger shaft connected with a preload spring. The outer housing unit configured to hold a micro actuator, cotter pins, locator pins to the micro actuator, and a push pull key.

Robotic gripper for writing and object creation

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Noida, India

Aniruddha Singhal