An optimization framework for simulation and kinematic control of Constrained Collaborative Mobile Agents (CCMA) system We present a concept of constrained collaborative mobile agents (CCMA) system, which consists of multiple wheeled mobile agents constrained by a passive kinematic chain. This mobile robotic system is modular in nature, the passive kinematic chain can be easily replaced with different designs and morphologies for different functions and task adaptability. Depending solely on the actuation of the mobile agents, this mobile robotic system can manipulate or position an endeffector. However, the complexity of the system due to presence of several mobile agents, passivity of the kinematic chain and the nature of the constrained collaborative manipulation requires development of an optimization framework. We therefore present an optimization framework for forward simulation and kinematic control of this system. With this optimization framework, the number of deployed mobile agents, actuation schemes, the design and morphology of the passive kinematic chain can be easily changed, which reinforces the modularity and collaborative aspects of the mobile robotic system. We present results, in simulation, for spatial 4DOF to 6DOF CCMA system examples. Finally, we present experimental quantitative results for two different fabricated 4DOF prototypes, which demonstrate different actuation schemes, control and collaborative manipulation of an endeffector.

MultiRobot Assembly Sequencing via Discrete Optimization Multirobot assembly has the potential to greatly reduce the cost and risk associated with the fabrication of large structures. Using teams of robots to perform assembly offers numerous advantages such as parallelism, robustness to singleagent failures, and flexibility in scheduling and task assignment. However, while previous work on multirobot assembly focuses on generating feasible assembly plans and decentralized control strategies, we instead study the problem of planning optimal assembly sequences.To this end, we pose the problem of multirobot assembly as a discrete optimization, specifically an integer linear program (ILP) or quadratic program (IQP), which aims to minimize the time to complete the assembly, or to minimize the distance traveled. We develop a model of multirobot assembly that captures both geometric constraints and actuation constraints inherent to the problem. While the ILP and IQP can be solved exactly using commercial optimization software in a substantial amount of time, we also propose heuristic strategies which can be quickly computed, and can scale to structures of reasonable size. We also verify our methods empirically by comparing their performance on a variety of test structures.