Position 1: under Asian Smart Cities Research and Innovation Network (ASCRIN) in collaboration with BITS Pilani and La Trobe University, Melbourne Australia,

Title of the project: “Low-cost empathetic robotic solution for caregiving (LERSCe)”.

Abstract: Australia and India have an elderly population which is rapidly growing. Studies indicate that almost half of the current population of over 75’s suffer from physical and/or mental impairments and as a result are in need of a high level of care. With an increasing elderly population and limited healthcare professionals, automated AI-aided health caregiving services offer a scalable solution to cope. Moreover, these solutions can be made efficient and cost-effective. One key service area where need outstrips human resources is in the delivery of remote physiotherapy. This project proposes to develop a novel soft-robotic actuator for the purpose of delivering remote physiotherapy in the home. A closed loop edge AI framework will drive the actuators to optimize service delivery. The edge framework will be self-contained to address privacy and security concerns. Control models will be trained offline and run locally on edge-capable devices. Machine learning methods, such as deep learning, will be explored to optimize actuator operations for maximum comfort and service efficacy. The feedback loop may include facial and audio expressions and information from other sensors such as skin resistance and
pressure to measure performance. Hence, there are two distinct aspects of the project: 1) the development of a lightweight, low-cost soft-robotic actuator 2) the development of an actuator control model which factors user behaviour and emotional feedback. Feedback may be derived from a suite of multimodal sensors including, but not limited to vision, tactile, and skin resistance.

Position 2: funded by BITS Cross-disciplinary Research Funding (CDRF)

Abstract:  The aim of this project is to develop a robotic manipulator system that can be safely employed with human workers and which can effectively coordinate with them.  This would require an interdisciplinary approach towards System Design, Control Law Design and Brain Computer Interface (BCI). A 3-DoF robotic manipulator model with flexible joints and torque controlled actuators will be designed. Then incorporate improved user-machine adaptation algorithms in a BCI.

Position 3 and 4: funded by TiH-ISI Kolkata