Recent technological advances enable gripper-equipped robots to perform many tasks traditionally associated with the human hand, allowing the use of grippers in a wide range of applications. Depending on the application, an ideal gripper design should be affordable, energy-efficient, and adaptable to many situations. However, regardless of the number of grippers available on the market, there are still many tasks that are difficult for grippers to perform, which indicates the demand and room for new designs to compete with the human hand. Thus, this paper provides a comprehensive review of robotic arm grippers to identify the benefits and drawbacks of various gripper designs. The research compares gripper designs by considering the actuation mechanism, degrees of freedom, grasping capabilities with multiple objects, and applications, concluding which should be the gripper design with the broader set of capabilities.

The number of individuals with upper or lower extremities dysfunction (ULED) has considerably increased in the past decades resulting in a high economic burden the families and society. Individuals with ULEDs require assistive robots to fulfill all their activities of daily living (ADLs). Thus, this research presents an objective function for base placement optimization of assistive robots to increase the workspace required to fulfill ADLs (workspace coverage). The workspace coverage was determined using the X-arm robot and experimenting with different ADLs. Also, an object collision algorithm is implemented to avoid collisions between the robot and the user within the workspace. Moreover, the algorithm determines the existence of singularities within the workspace by computing the manipulability index. However, since the manipulability index computation depends on the Jacobian matrix’s eigenvalues yielding incongruences in the units, we divided the Jacobian matrix into two parts; one for the angular and another for the linear velocity. Finally, using the objective function with a genetic algorithm (GA), the optimal base placement for the robot is obtained and validated experimentally.

The number of individuals with upper or lower extremities dysfunction (ULED) has considerably increased in the past few decades, resulting in a high economic burden for their families and society. Individuals with ULEDs require assistive robots to fulfill all their activities of daily living (ADLs). However, a theory for the optimal design of assistive robots that reduces energy consumption while increasing the workspace is unavailable. Thus, this research presents an algorithm for the optimal link length selection of an assistive robot mounted on a wheelchair to minimize the torque demands of each joint while increasing the workspace coverage. For this purpose, this research developed a workspace to satisfy a list of 18 ADLs. Then, three torque indices from the literature were considered as performance measures to minimize; the three torque measures are the quadratic average torque (QAT), the weighted root square mean (WRMS), and the absolute sum of torques (AST). The proposed algorithm evaluates any of the three torque measures within the workspace, given the robot dimensions. This proposed algorithm acts as an objective function, which is optimized using a genetic algorithm for each torque measure. The results show that all tree torque measures are suitable criteria for assistance robot optimization. However, each torque measures yield different optimal results; in the case of the QAT optimization, it produces the least workspace with the minimum overall torques of all the joints. Contrarily, the WRMS and AST optimization yield similar results generating the maximum workspace coverage but with a greater overall torque of all joints. Thus, the selection between the three methods depends on the designer’s criteria. Based on the results, the presented methodology is a reliable tool for the optimal dimensioning of assistive robots.

Parallel mechanisms with reduced degree of freedom (DOF) have grown in importancefor industry and researchers as they o er a simpler architecture and lower manufactur-ing/operating costs with great performance. In this paper, a two degree of freedomparallel robot is proposed and analyzed. The robot with a xed base, a moving platformand three legs achieve translational and rotational motion through actuation on prismaticand revolute joints, and can be applied on pick and place applications, vehicle simulatorsamong others. By making use of homogeneous transformation matrices and Sylvestersdialytic elimination method a closed form solution for direct kinematics is obtained forall possible assembly modes. Inverse kinematics was solved in closed form as well. Thisgreatly decreases computational time and proposed approach is optimal. A case studywas done to validate the solutions found and compared with a CAD model to corroborateresults. Finally, a workspace calculation was made for di erent geometrical parametersof the robot.

Robot-Assisted Gait Training (RAGT) has emerged as a promising approach to improve motor recovery for stroke survivors. Among RAGT devices, exoskeletons offer precise joint actuation, but they are costly, mechanically complex and present risks related to joint misalignment. End-effector systems present a more affordable and simpler alternative, but face limitations in workspace and adaptability for assist-as-needed therapy. Cable-Driven End-Effector Gait Rehabilitation Robots (CDEGRs) combine the strengths of both approaches, offering low inertia, flexible configurations, and scalable designs. This review systematically examines the current landscape of CDEGRs, encompassing their kinematic classifications, control strategies, and platform configurations. Unlike previous reviews that broadly addressed exoskeletons or upper-limb rehabilitation devices, this work provides a focused and detailed analysis of lower-limb end-effector systems. In doing so, it identifies persistent gaps in design and control frameworks and highlights future research directions toward more efficient and clinically validated CDEGR architectures.