Coordinated multi-arm motion planning: Reaching for moving objects in the face of uncertainty

Abstract

Abstract-Coordinated control strategies for multi-robot systems are necessary for tasks that cannot be executed by a single robot. This encompasses tasks where the workspace of the robot is too small or where the load is too heavy for one robot to handle. Using multiple robots makes the task feasible by extending the workspace and/or increase the payload of the overall robotic system. In this paper, we consider two instances of such tasks: a co-worker scenario in which a human hands over a large object to a robot; intercepting a large flying object. The problem is made difficult as the pick-up/intercept motions must take place while the object is in motion and because the object's motion is not deterministic. The challenge is then to adapt the motion of the robotic arms in coordination with one another and with the object. Determining the pick-up/intercept point is done by taking into account the workspace of the multi-arm system. The point is continuously recomputed to adapt to change in the object's trajectory. We propose a virtual object based dynamical systems (DS) control law to generate autonomous and synchronized motions for a multi-arm robot system. We show theoretically that the multi-arm + virtual object system converges asymptotically to the moving object. We validate our approach on a dual-arm robotic system and demonstrate that it can resynchronize and adapt the motion of each arm in a fraction of a second, even when the motion of the object is fast and not accurately predictable.

Planning to repose long and heavy objects considering a combination of regrasp and constrained drooping

“…Those methods assume that a single robot is not enough to get such tasks done and use multiple robots for help. For example, a method for coordinating a multi-arm system’s motion to receive an object from a human handover was proposed in Sina Mirrazavi Salehian et al (2016). In Xian et al (2017), the authors explored the changes in the configuration space connectivity when the multi-arm system work together in a closed chain to manipulate a large object.…”

“…Previously, researchers considered overcoming the problem by using multiple robots to share object weight. The examples include but are not limit to using multiple arms (Sina Mirrazavi Salehian et al , 2016; Xian et al , 2017; Dehio et al , 2018), multiple mobile robots (Yamashita et al , 1998), multiple mobile manipulators (Alipour and Moosavian, 2011) or a combination of robots and other machines (Ohashi et al , 2016). The drawback is using multiple robots that decrease the overall automation system’s efficiency because of the high costs.…”

dRRT*: Scalable and informed asymptotically-optimal multi-robot motion planning

“…Furthermore, force control strategies are helpful for multi-arm manipulation of a common object (Caccavale and Uchiyama, 2008). Recently coordinated control has been applied to solve human-robot interaction tasks (Sina Mirrazavi Salehian et al, 2016).…”

Dual-Arm Coordinated Motion Planning and Compliance Control for Capturing Moving Objects with Large Momentum

“…Salehian et al [5] proposed a coordinated multi-arm motion planning method for reaching moving objects with motion uncertainty, which can generate autonomous and synchronized motions using the virtual object based dynamic system. A similar dynamic system is also used to catch a flying object softly [6].…”

“…A similar dynamic system is also used to catch a flying object softly [6]. However, the momentum transfer was bypassed by assuming the large object moves very slowly in [5] and the flying object has a negligible mass in [6]. The internal force analysis and load distribution for cooperative manipulation have been studied in [7], [8].…”