Practical analytical inverse kinematic approach for 7-DOF space manipulators with joint and attitude limits

Toward coordinated planning and hierarchical optimization control for highly redundant mobile manipulator

This paper represents a constraint planning and optimization control scheme for a highly redundant mobile manipulator considering a complex indoor environment. Compared with the traditional optimization solution of a redundant manipulator, infinity norm and slack variable are additionally introduced and leveraged by the optimization algorithm. The former takes into account the joint limits effectively by considering individual joint velocities and the latter relaxes the equality constraint by decreasing the infeasible solution area. By using derived kinematic equations, the tracking control problem is expressed as an optimization problem and converted into a new quadratic programming (QP) problem. To address the optimization problem, the two-timescale recurrent neural networks optimization scheme is proposed and tested with a 9 DOFs nonholonomic mobile-based manipulator. Additionally, the BI2RRT∗ path-planning algorithm incorporates path planning in the complex environment where different obstacles are positioned. To test and evaluate the proposed optimization scheme, both predefined and generated paths are tested in the Neurorobotics Platform (NRP) 2which is open access and open source integrative simulation framework powered by Gazebo and developed by our team.

An Analytical Solution for Inverse Kinematics of SSRMS-Type Redundant Manipulators

Compared with non-redundant manipulators, the self-motion of 7-DOF redundant manipulators results in an infinite number of inverse kinematics solutions for a desired end-effector pose. This paper proposes an efficient and accurate analytical solution for inverse kinematics of SSRMS-type redundant manipulators. This solution is applicable to SRS-type manipulators with the same configuration. The proposed method involves introducing an alignment constraint to restrain the self-motion and to decompose the spatial inverse kinematics problem into three independent planar subproblems simultaneously. The resulting geometric equations depend on the part of the joint angles, respectively. These equations are then computed recursively and efficiently using the sequences of (θ1,θ7), (θ2,θ6), and (θ3,θ4,θ5), generating up to sixteen sets of solutions for a given desired end-effector pose. Additionally, two complementary methods are proposed for overcoming the possible singular configuration and judging unsolvable poses. Finally, numerical simulations are conducted to investigate the performance of the proposed approach in terms of average calculation time, success rate, average position error, and the ability to plan a trajectory with singular configurations.

Trajectory tracking control of 7-DOF redundant robot based on estimation of intention in physical human-robot interaction

Collaborative robot has been widespread application prospect, such as homes, manufacturing, and health-care etc. In physical human-robot interaction, the external force appears inevitably in contact with environment or human, especially the interactive tasks such as trajectory tracking requirements and force compliance control. In this article, a method based on interaction intention estimation, which solve the problem of trajectory tracking accuracy and force compliance control in the same direction for the 7-DOF robot, is proposed. The increased virtual force depended on the manipuility performance index and inverse kinematic solution used the kinematic decoupling method based on the redundant angle avoid the singularity of redundant robot. Then, based on interactive intention estimation, a control strategy of variable impedance sliding mode theory in the presence of virtual force and contact force is proposed to achieve the trajectory tracking. We adopted hyperbolic tangent function to alleviate the chattering problem caused by switch function and validated the control system stability by Lyapunov theorem. Finally, Matlab simulations exhibit a 97.8% of high tracking accuracy amid the external force is 43% less than variable impedance parameters. It is therefore proved that the proposed method can achieve asymptotic tracking and the compliant behavior in physical human-robot interaction.

Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm

This work addresses the multitask-based trajectory-planning problem (MTTP) for space robotics, which is an emerging application of successively executing tasks in assembly of the International Space Station. The MTTP is transformed into a parameter-optimization problem, where piecewise continuous-sine functions are employed to depict the joint trajectories. An improved genetic algorithm (IGA) is developed to optimize the unknown parameters. In the IGA, each chromosome consists of three parts, namely the waypoint sequence, the sequence of the joint configurations, and a special value for the depiction of the joint trajectories. Numerical simulations, including comparisons with two other approaches, are developed to test IGA validity.

Kinematic analysis and fault-tolerant trajectory planning of space manipulator under a single joint failure

A space manipulator plays an important role in spacecraft capturing, repairing, maintenance, and so on. However, the harsh space environment will cause its joints fail to work. For a non-redundant manipulator, single joint locked failure will cause it to lose one degree of freedom (DOF), hence reducing its movement ability. In this paper, the key problems related to the fault-tolerant including kinematics, workspace, and trajectory planning of a non-redundant space manipulator under single joint failure are handled. First, the analytical inverse kinematics equations are derived for the 5-DOF manipulator formed by locking the failure joint of the original 6-DOF manipulator. Then, the reachable end-effector pose (position and orientation) is determined. Further, we define the missions can be completed by the 5-DOF manipulator. According to the constraints of the on-orbital mission, we determine the grasp envelope required for the end-effector. Combining the manipulability of the manipulator and the performance of its end-effector, a fault tolerance parameter is defined and a planning method is proposed to generate the reasonable trajectory, based on which the 5-DOF manipulator can complete the desired tasks. Finally, typical cases are simulated and the simulation results verify the proposed method.

Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm

With the development of aerospace engineering, the space on-orbit servicing has been brought more attention to many scholars. Obstacle avoidance planning of space manipulator end-effector also attracts increasing attention. This problem is complex due to the existence of obstacles. Therefore, it is essential to avoid obstacles in order to improve planning of space manipulator end-effector. In this paper, we proposed an improved ant colony algorithm to solve this problem, which is effective and simple. Firstly, the models were established respectively, including the kinematic model of space manipulator and expression of valid path in space environment. Secondly, we described an improved ant colony algorithm in detail, which can avoid trapping into local optimum. The search strategy, transfer rules, and pheromone update methods were all adjusted. Finally, the improved ant colony algorithm was compared with the classic ant colony algorithm through the experiments. The simulation results verify the correctness and effectiveness of the proposed algorithm.