Silent underwater actuation and object detection are desired for certain applications in environmental monitoring. However, several challenges need to be faced when addressing simultaneously the issues of actuation and object detection using vision system. This paper presents a swimming underwater soft robot inspired by the moon jellyfish (Aurelia aurita) species and other similar robots; however, this robot uniquely utilizes novel artificial muscles and incorporates camera for visual information processing. The actuation characteristics of the novel artificial muscles in water are presented which can be used for any other applications. The bio-inspired robot, Jelly-Z, has the following characteristics: (1) The integration of three 60 mm-long twisted, and coiled polymer fishing line (TCPFL) muscles in a silicone bell to achieve contraction and expansion motions for swimming; (2) A Jevois camera is mounted on Jelly-Z to perform object detection while swimming using a pre-trained neural network; (3) Jelly-Z weighs a total of 215 g with all its components and is capable of swimming 360 mm in 63 seconds. The present work shows, for the first time, the integration of camera detection and TCPFL actuators in an underwater soft jellyfish robot, and the associated performance characteristics. This kind of robot can be a good platform for monitoring of aquatic environment either for detection of objects by estimating the percentage of similarity to pre-trained network or by mounting sensors to monitor water quality when fully developed.

Real-time monitoring of water quality in the river Ganga and other Indian rivers is crucial to determining its suitability for drinking and other usages across the seasons and round the clock. For this, a structurally strong and hydrostatically stable floating observation center is required to house all the sensors and related equipment. This paper explains the design process for such a buoy platform that can house an array of water quality sensors powered by hybrid energy harvesting systems. Sensors are connected to a wireless sensor network (WSN) system that transfers data to a web-based platform, where we can monitor and analyze our data for the purpose of hazard prediction. Computational analysis has been carried out for the observatory body to ascertain its structural integrity and hydrostatic stability at small and large angles of inclination. The buoy design is based on various requirements specific to Indian rivers at different locations from the mid-course to the confluence. It is important that the system be modular and portable for use in a constantly changing river/water environment. A full-scale functional prototype has been developed, and field testing has been carried out to bring out the efficacy of the proposed system. Also, the WSN system collected real-time water quality data that have been validated with laboratory-based experiments. The establishment of a network of low-cost river/water health monitoring system will further initiate the large-scale data collection and help create digital twins of the Indian rivers.

In this paper, a new socially assistive robot (SARs) called HBS-1.2 is presented, which uses 6-ply twisted and coiled polymer (TCP) artificial muscles in its hand to perform physical tasks. The utilization of 6-ply TCP artificial muscles in a humanoid robot hand is a pioneering advancement, offering cost effective, lightweight, and compact solution for SARs. The robot is designed to provide safer human–robot interaction (HRI) while performing physical tasks. The paper explains the procedures for fabrication and testing of the 6-ply TCP artificial muscles, along with improving the actuation response by using a Proportional-Integral-Derivative (PID) control method. Notably, the robot successfully performed a vision-based pick and place experiment, showing its potential for use in homecare and other settings to assist patients who suffer from neurological diseases like Alzheimer’s disease. The study also found an optimal light intensity range between 34 to 108 lumens/m², which ensures minimal variation in calculated distance with 95% confidence intervals for robust performance from the vison system. The findings of this study have important implications for the development of affordable and accessible robotic systems to support elderly patients with dementia, and future research should focus on further improving the use of TCP actuators in robotics.

In this paper, we present a novel multilayered morphing structure, having similar topology resembling the structures found in nature to grasp delicate objects effectively as well as sense contact force and temperature. The structure consists of two actuation layers, two U-shaped cooling channel layers, piezoelectric based touch sensors and temperature sensors. Employing shape memory alloy (SMA) spring actuators for bending and twisted and coiled polymer fishing line with nichrome (TCP_FL ^NMC) artificial muscles for antagonistic return, the soft silicone-based composite skin exhibits unique capabilities of large bidirectional movement, avoid rigid passive springs for return motion, soft grasping, safe interaction with humans, and ease fabrication. The SMA (0.38 mm wire diameter) serves as relatively fast actuating muscle and the TCP_FL ^NMC (0.8 mm fiber diameter) as a slow actuating (considering mainly heating cycle), which was programmed/designed to mimic the fast and slow twitching muscles found in nature. Bending and return operations of skin samples of length 100 mm and thickness of 9 mm, with three different widths 20 mm, 25 mm, 30 mm, were experimentally studied. The 25 mm wide multilayered soft skin demonstrated cyclic actuation with a maximum bending angle of ∼70°, which was attributed due to the active cooling. The fluidic channels for active cooling were fabricated using 3D printed PVA tubes, casting within the silicone in a mold and subsequently dissolving in a circulating water. The study also included the integration and voltage response of mini-piezodisk sensor PIC255 having a diameter of 2 mm and thickness of 0.15 mm, which was embedded at different depths within the silicone (on the surface, 1 mm depth and 2 mm depth). The multilayered soft skin was also able to detect the temperature of the object during grasping, suggesting its potential application as a soft gripper in robotic systems.