An Automatic Self Shape-Shifting Soft Mobile Robot (A4SMR)

This article proposes a mobile robot that is fully constructed and actuated by utilising a pneumatic artificial muscle (PAM). Several features are shown in this design including softness, lightweight, and shape change. The robot that has been designed in this article is constructed with four identical contraction actuators: one pair for steering and moving forward and the second pair for shape-shifting. The proposed mobile robot has the ability to move forward, steer, and shapeshift to navigate through narrow paths. The kinematic for the system is provided for the area of the robot by using the shoelace formula by utilising a Pixy camera to track the coordinates of the four vertices

Design, implementation and modelling of the single and multiple extensor pneumatic muscle actuators

The soft actuator represents a valuable addition to the robotics research area in last two decades. These actuators provide significant features such as lightweight, softness, high force to weight ratio and the ability to form in different shapes. This article presents a new length model to the single extensor pneumatic muscle actuator (PMA) which is depended on the constructed parameters and the air pressure. On the other hand, the tensile force formula of the contractor actuator has been modified to describe the extension force of the extensor PMA. The parallel structure of four extensor actuators is designed and implemented as continuum arm. The bending behaviour of the proposed arm is illustrated and modelled mathematically. The length model of the single extensor actuator has validated by the comparison between the model and the experiment data and then a neural network (NN) control system is applied to control the elongation of the extensor PMA. The kinematics for the proposed continuum arm are presented to describe the bending of the arm and its direction

Vision-Based Soft Mobile Robot Inspired by Silkworm Body and Movement Behavior

Designing an inexpensive, low-noise, safe for individual, mobile robot with an efficient vision system represents a challenge. This paper proposes a soft mobile robot inspired by the silkworm body structure and moving behavior. Two identical pneumatic artificial muscles (PAM) have been used to design the body of the robot by sewing the PAMs longitudinally. The proposed robot moves forward, left, and right in steps depending on the relative contraction ratio of the actuators. The connection between the two artificial muscles gives the steering performance at different air pressures of each PAM. A camera (eye) integrated into the proposed soft robot helps it to control its motion and direction. The silkworm soft robot detects a specific object and tracks it continuously. The proposed vision system is used to help with automatic tracking based on deep learning platforms with real-time live IR camera. The object detection platform, named, YOLOv3 is used effectively to solve the challenge of detecting high-speed tiny objects like Tennis balls. The model is trained with a dataset consisting of images of   Tennis balls. The work is simulated with Google Colab and then tested in real-time on an embedded device mated with a fast GPU called Jetson Nano development kit. The presented object follower robot is cheap, fast-tracking, and friendly to the environment. The system reaches a 99% accuracy rate during training and testing. Validation results are obtained and recorded to prove the effectiveness of this novel silkworm soft robot. The research contribution is designing and implementing a soft mobile robot with an effective vision system

Synthesis and Thermal Characterization of Copolymers Containing Amino Acids

Thee copolymers of amino acid were synthesized in two steps. First, the amino acids react with resorcinol to formation of azo monomers step. They led in a second condensation polymerization step to copolymeric materials. The structures of the copolymers were characterized by means of FT-IR and 1H-NMR spectroscopy. The thermal properties were investigated by TGA and DTG. Keywords: copolymers, amino acid, thermal properties, azo compoun

Design, Implementation, and Kinematics of a Twisting Robot Continuum Arm Inspired by Human Forearm Movements

In this article, a soft robot arm that has the ability to twist in two directions is designed. This continuum arm is inspired by the twisting movements of the human upper limb. In this novel continuum arm, two contractor pneumatic muscle actuators (PMA) are used in parallel, and a self-bending contraction actuator (SBCA) is laid between them to establish the twisting movement. The proposed soft robot arm has additional features, such as the ability to contract and bend in multiple directions. The kinematics for the proposed arm is presented to describe the position of the distal end centre according to the dimensions and positions of the actuators and the bending angle of the SBCA in different pressurized conditions. Then, the rotation behaviour is controlled by a high precision controller system

Adaptive Vector Field Histogram Plus (VFH+) Algorithm using Fuzzy Logic in Motion Planning for Quadcopter

This work introduces the adaptive version of the vector field histogram plus (VFH+) motion planning algorithm, which is designed for unmanned aerial vehicles, particularly quadcopters, to enhance its performance in navigation tasks. The method suggests incorporating fuzzy control to adaptively modify the VFH+ look-ahead distance parameter by analysis continuous environmental and motion conditions. Simulation tests were completed using different scenarios that varied in obstacle quantity, density, distribution, and size and waypoint quantity. Simulation results showed the successful outcomes of this strategy in enhancing quadcopter motion performance in various contexts. The results indicated notable enhancements in obstacle avoidance, smoother motion trajectories, and decreased travel time compared to the traditional VFH+ method. One of the most important aspects of creating real-time motion planning systems is handling uncertainty. This is accomplished by incorporating a fuzzy system knowledge base for automatic algorithmic modification into the planning process and employing advanced motion-planning techniques. The adaptive algorithm improves the quadcopter's ability to deal with high uncertainty levels by incorporating fuzzy logic for dynamic parameter adjustment, allowing for accurate and efficient navigation in various environments, even in uncertain conditions