Grasping a variety of objects remains a key challenge in the development of versatile robotic systems. The human hand is remarkably dexterous, capable of grasping and manipulating objects with diverse shapes, mechanical properties, and textures. Inspired by how humans use two fingers to pick up thin and large objects such as fabric or sheets of paper, we aim to develop a gripper optimized for grasping such deformable objects. Observing how the soft and flexible fingertip joints of the hand approach and grasp thin materials, a hybrid gripper design that incorporates both soft and rigid components was proposed. The gripper utilizes a soft pneumatic ring wrapped around a rigid revolute joint to create a flexible two-fingered gripper. Experiments were conducted to characterize and evaluate the gripper's performance in handling sheets of paper and other objects. Compared to rigid grippers, the proposed design improves grasping efficiency and reduces the gripping distance by up to eightfold.

This article studies a leader-follower formation algorithm based on fractional order proportional-derivative (FOPD) controller for multiple unmanned aerial vehicles (UAVs) when tackling an emergency health case. The controller parameters are tuned by using a particle swarm optimization (PSO) algorithm. Its performance is compared with an integer order proportional-derivative (IOPD) controller. Finally, the global path planning for the UAVs swarm is found by using a Dijkstra's algorithm with quintic polynomial trajectory. This provides an optimal global path by considering the physical system dimension and constraints of acceleration and velocity of the UAV. The simulation tests using the virtual environment demonstrate that the proposed approach outperforms the IOPD controller.

Shallow geophysics have become an important tool in archaeological prospection (i.e. the investigation of archaeological remains without recurring to excavations). This paper presents the conceptual study for speed control of geophysical measurement platform for archaeological prospection on challenging terrain using a fuzzy logic approach. A traversal-terrain speed behavior is introduced to have suitable platform movement on the interested terrain regions. The regional traverse-terrain behavior is complemented by following behaviors: traversal terrain behaviors, local obstacle avoiding and geophysical investigating behavior. The fuzzy based speed control strategy has several advantages. Firstly, the fuzzy logic rules that govern the autonomous geophysical measurement platform (AGMP) motion are simpler and more understandable since it can emulate the archaeologist drivers knowledge and experience. Secondly, the behavior-based strategy has a modular structure that can be extended to incorporate new behaviors. The experiments are implemented on a Lego robot to test the proposed approach.