Distributed cooperative manipulation under timed temporal specifications

Abstract

This paper addresses the problem of cooperative manipulation of a single object by N robotic agents under local goal specifications given as Metric Interval Temporal Logic (MITL) formulas. In particular, we propose a distributed model-free control protocol for the trajectory tracking of the cooperatively manipulated object without necessitating feedback of the contact forces/torques or inter-agent communication. This allows us to abstract the motion of the coupled object-agents system as a finite transition system and, by employing standard automata-based methodologies, we derive a hybrid control algorithm for the satisfaction of a given MITL formula. In addition, we use load sharing coefficients to represent potential differences in power capabilities among the agents. Finally, simulation studies verify the validity of the proposed scheme.

Timed abstractions for distributed cooperative manipulation

“…This paper extends our previous work (Verginis and Dimarogonas 2016) in the following directions: firstly, we express the dynamic models of the object and the agents by employing angular velocities and accelerations for the agents' end-effector and the object's center of mass (contrary to Euler angle accelerations used in Verginis and Dimarogonas (2016)). This is more accurate for real-time scenarios and also introduces the realistic problem of representation singularities for the object's center of mass, which is resolved by our control methodology.…”

Communication-based Decentralized Cooperative Object Transportation Using Nonlinear Model Predictive Control

“…Each agent, after solving its optimization problem, transmits its calculated predicted variables to the agents of lower priority, which take them into account for collision avoidance. Note that the coupled object-agent dynamics are implicitly taken into account in equations ( 14), (15) in the following sense. Although the coupled model (13) does not imply that each one of these equations is satisfied, by forcing each agent to comply with the specific dynamics through the optimization procedure, we guarantee that (13) is satisfied, since it's the result of the addition of ( 14) and ( 15), for every i = 1 and i ∈ {2, .…”

“…These methodologies, however, may suffer from local minima, even in single-agent cases, and in many cases they yield high control inputs that do not comply with the saturation of actual motor inputs, especially close to collision configurations. In our previous works, [15], [16], we considered the problem of trajectory tracking for decentralized robust cooperative manipulation, without taking into account singularity-or collision avoidance.…”

Reconfigurable Motion Planning and Control in Obstacle Cluttered Environments under Timed Temporal Tasks

“…Ultimately, however, we are interested in complex tasks over predefined time horizons ("collect data in region C every 50 seconds and upload it in region D after at most 10 seconds"), which can be encompassed by timed temporal languages (e.g., Metric Temporal Logic) [14]. Timed temporal tasks have been considered in a variety of works in the related literature [12], [15]- [23]. The authors in [21], [22] as Metric Interval Temporal Logic (MITL) formulas, based on reachibility analysis performed on the discretized state space.…”

“…In [19] the authors use predetermined open-loop controllers to transition in a partitioned workspace according to a high-level plan satisfying an MITL formula determined through formal verification techniques. MITL specifications are also considered in [12], [23], where robust closedform controllers that guarantee the timed navigation of a cooperatively manipulated object in a partitioned workspace are derived. [18] proposes a roadmap abstraction-based algorithm to address the problem of multi-goal motion planning under time windows.…”