Motion Planning for 6-D Manipulation with Aerial Towed-cable Systems

Abstract

Abstract-Performing aerial 6-dimensional manipulation using flying robots is a challenging problem, to which only little work has been devoted. This paper proposes a motion planning approach for the reliable 6-dimensional quasi-static manipulation with an aerial towed-cable system. The novelty of this approach lies in the use of a cost-based motion-planning algorithm together with some results deriving from the static analysis of cabledriven manipulators. Based on the so-called wrench-feasibility constraints applied to the cable tensions, as well as thrust constraints applied to the flying robots, we formally characterize the set of feasible configurations of the system. Besides, the expression of these constraints leads to a criterion to evaluate the quality of a configuration. This allows us to define a cost function over the configuration space, which we exploit to compute good-quality paths using the T-RRT algorithm. As part of our approach, we also propose an aerial towed-cable system that we name the FlyCrane. It consists of a platform attached to three flying robots using six fixed-length cables. We validate the proposed approach on two simulated 6-D quasi-static manipulation problems involving such a system, and show the benefit of taking the cost function into account for such motion planning tasks.

Dynamic collaboration without communication: Vision-based cable-suspended load transport with two quadrotors

“…We denote as a and b the x and y coefficients of p. The force exerted by the quadrotor is denoted by f . beyond quasi-static object manipulation [5], [14], [15].…”

Aerial robotic contact-based inspection: planning and control

“…A variety of research groups have put their efforts and recent contributions include interesting lightweight manipulator designs and model-free or model-based control methods such as those in Jiang and Voyles (2013), Parra-Vega et al (2013), Gioioso et al (2014), Orsag et al (2013Orsag et al ( , 2014, , Bellens et al (2012), Fumagalli et al (2014), Huber et al (2013), Mellinger et al (2011Mellinger et al ( , 2013, Marconi and Naldi (2012), Marconi et al (2011), Srikanth et al (2011, Pounds et al (2011), Papachristos and Tzes (2013), Sreenath and Kumar (2013), Montserrat Manubens et al (2013), Manubens et al (2013). Based on these and other relevant efforts, it has been shown that an aerial robot, although a floating manipulating base, has the capacity to ensure stable physical interaction and a variety of tasks including grasping or position-controlled force tracking can be conducted.…”

Efficient Sampling-Based Approaches to Optimal Path Planning in Complex Cost Spaces

“…When high-clearance paths are desirable, the cost of a configuration can be the inverse of the distance between the robot and the closest obstacle [4], [10]. Even more complex cost functions can appear in robotic problems [2], [16] and structural-biology problems [9].…”