A General Framework for Hierarchical Redundancy Resolution Under Arbitrary Constraints

Fiore, Mario D.; Meli, Gaetano; Ziese, Anton; Siciliano, Bruno; Natale, Ciro

doi:10.1109/tro.2022.3232266

Cited by 10 publications

(4 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, with the development of robotic object perception [ 30 , 31 , 32 ], the mobile manipulator could build a small-scale representation of the environment around itself with more object information, which would be very helpful to deal with complex 3D environments and have better manipulation capabilities. In addition, the manipulation task introduces many constraints to the motion planning, therefore, the whole-body motion planning method including redundancy resolution [ 33 ] and base position optimizition [ 34 ] has the potential to be added to our proposed method to plan a path satisfying various constraints introduced by the environment and the manipulation task. Furthermore, the real-time whole-body planning method is another issue that deserves further attention.…”

Section: Discussionmentioning

confidence: 99%

A Hierarchical Motion Planning Method for Mobile Manipulator

Chen,

Zang,

Liu

et al. 2023

Sensors

View full text Add to dashboard Cite

This paper focuses on motion planning for mobile manipulators, which includes planning for both the mobile base and the manipulator. A hierarchical motion planner is proposed that allows the manipulator to change its configuration autonomously in real time as needed. The planner has two levels: global planning for the mobile base in two dimensions and local planning for both the mobile base and the manipulator in three dimensions. The planner first generates a path for the mobile base using an optimized A* algorithm. As the mobile base moves along the path with the manipulator configuration unchanged, potential collisions between the manipulator and the environment are checked using the environment data obtained from the on-board sensors. If the current manipulator configuration is in a potential collision, a new manipulator configuration is searched. A sampling-based heuristic algorithm is used to effectively find a collision-free configuration for the manipulator. The experimental results in simulation environments proved that our heuristic sampling-based algorithm outperforms the conservative random sampling-based method in terms of computation time, percentage of successful attempts, and the quality of the generated configuration. Compared with traditional methods, our motion planning method could deal with 3D obstacles, avoid large memory requirements, and does not require a long time to generate a global plan.

show abstract

Section: Discussionmentioning

confidence: 99%

A Hierarchical Motion Planning Method for Mobile Manipulator

Chen,

Zang,

Liu

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…The SNS method can achieve obstacle avoidance by adapting limits of joint velocities near obstacles [22] or by augmenting joint velocities with velocities of control points on links of the manipulator and limiting these velocities in the vicinity of obstacles [23]. The SNS method is usually formulated at the velocity level, but it has been extended in [24,25] to function also at acceleration and torque levels.…”

Section: Generalized-inverse-velocity-based Kinematic Control and Obs...mentioning

confidence: 99%

“…which means that the outboard endpoint of the manipulator must describe the desired path given by the first two coordinates of Equation ( 25), and the last link maintains a constant orientation given by the last coordinate of Equation (25). The desired path is displayed in Figure 10.…”

Section: Generalized-inverse-velocity Output Tracking and Obstacle Av...mentioning

confidence: 99%

“…The path-planning obstacle avoidance problem is first treated using the differentiable manifold algorithm of Section 3.3 with a time step of ∆t = 0.001 s, which results in the sequence of postures shown in Figure 11 (supplementary video S3 is attached that illustrates the continuous motion). As demonstrated by Figure 11, the algorithm is able to resolve redundancy and obtain a feasible motion that tracks the desired output trajectory of Equation (25), while avoiding penetration of all obstacles for all time. First, the manipulator contacts obstacle O1 (Figure 11b), and then it contacts obstacle O2 (Figure 11c-d), to lose contact later (Figure 11e-h).…”

Section: Differentiable-manifold Output Tracking and Obstacle Avoidancementioning

confidence: 99%

See 1 more Smart Citation

Obstacle Avoidance in Operational Configuration Space Kinematic Control of Redundant Serial Manipulators

Peidro,

Haug

2023

Machines

View full text Add to dashboard Cite

Kinematic control of redundant serial manipulators has been carried out for the past half century based primarily on a generalized inverse velocity formulation that is known to have mathematical deficiencies. A recently developed inverse kinematic configuration mapping is employed in an operational configuration space differentiable manifold formulation for redundant-manipulator kinematic control with obstacle avoidance. This formulation is shown to resolve deficiencies in the generalized inverse velocity formulation, especially for high-degree-of-redundancy manipulators. Tracking a specified output trajectory while avoiding obstacles for four- and twenty-degree-of-redundancy manipulators is carried out to demonstrate the effectiveness of the differentiable manifold approach for applications with a high degree of redundancy and to show that it indeed resolves deficiencies of the conventional generalized inverse velocity formulation in challenging applications.

show abstract