Mobile manipulation requires the integration of methodologies from all aspects of robotics. Instead of tackling each aspect in isolation,mobilemanipulation research exploits their interdependence to solve challenging problems. As a result, novel views of long-standing problems emerge. In this chapter, we present these emerging views in the areas of grasping, control, motion generation, learning, and perception. All of these areas must address the shared challenges of high-dimensionality, uncertainty, and task variability. The section on grasping and manipulation describes a trend towards actively leveraging contact and physical and dynamic interactions between hand, object, and environment. Research in control addresses the challenges of appropriately coupling mobility and manipulation. The field of motion generation increasingly blurs the boundaries between control and planning, leading to task-consistent motion in high-dimensional configuration spaces, even in dynamic and partially unknown environments. A key challenge of learning formobilemanipulation consists of identifying the appropriate priors, and we survey recent learning approaches to perception, grasping, motion, and manipulation. Finally, a discussion of promising methods in perception shows how concepts and methods from navigation and active perception are applied.
Exploitation of environmental constraints in human and robotic grasping
Author Clemens Eppner, Raphael Deimel, Jose Alvarez-Ruiz, Marianne Maertens, Oliver Brock
Video ID : 657
We investigate the premise that robust grasping performance is enabled by exploiting constraints present in the environment. Given this premise, grasping becomes a process of successive exploitation of environmental constraints, until a successful grasp has been established. We present evidence for this view by showing robust robotic grasping based on constraint-exploiting grasp strategies, and we show that it is possible to design robotic hands with inherent capabilities for the exploitation of environmental constraints.