In this paper, we present a novel trajectory planning method for externally-actuated modular manipulators (EAMMs), consisting of multiple rotor-actuated links with joints that can be either locked or unlocked. This joint-locking feature allows effective balancing of the payload capacity and dexterity of the robot but significantly complicates the planning problem by introducing binary decision variables. To address this challenge, we leverage the problem’s intrinsic structure, i.e., the payload at the end-effector being enhanced by merely locking its immediate connected links; this allows us to break down the complex planning problem into a series of manageable subproblems and solve them sequentially. Our approach significantly reduces the problem’s complexity: in a serial n-link EAMM with m joint-lock mechanisms, where there could potentially be 2mdistinct configurational dynamics, we require solving only n + 1 trajectory optimization problems for single rigid body dynamics sequentially, thereby rendering the problem tractable. We substantiate the efficacy of our method through various simulation and experimental studies, covering ground-free and ground-bound configurations as well as both motion-only and manipulation tasks.

The ability to grasp objects broadens the application range of unmanned aerial vehicles (UAVs) by allowing interactions with the environment. The difficulty in performing a midair grasp is the high probability of impact between the UAV's foot and the target. For a successful grasp, the foot must smoothly absorb the energy of impact and simultaneously engage with the target in a short period of time. We present a bioinspired passive dynamic foot in which the claws are actuated solely by the impact energy. Our gripper simultaneously resolves the issue of smooth absorption of the impact energy and fast closure of the claws by linking the motion of an ankle linkage and the claws through soft tendons. We study the dynamics of impact and use the stiffness of the tendon as our design/control parameter to adjust the mechanics of the gripper for smooth recycling of the impact energy. Our gripper closes within 45 ms after initial contact with the impacting object without requiring any controller or actuation energy. An electroadhesive locking mechanism attached to the tendon locks the claws within 20 ms after reaching closed configuration. We demonstrated the effectiveness of our gripper by integrating it in an UAV and performing a variety of passive dynamic perching and grasping tasks.

The RVM (Robot-based Vibration Suppression Modules) is proposed for the manipulation and transport of a large flexible object. Since the RVM is easily attachable/detachable to the object, this RVM allows distributing over the manipulated object so that it is scalable to the object size. The composition of the system is partly motivated by the MAGMaS (Multiple Aerial-Ground Manipulator System) [1]- [3], however, since the quadrotor usage is mechanically too complicated and its design is not optimized for manipulation, thus we overcome these limitations using distributed RVMs and newly developed theory. For this, we first provide a constrained optimization problem of RVM design with the minimum number of rotors, so that the feasible thrust force is maximized while it minimizes undesirable wrench and its own weight. Then, we derive the full dynamics and elucidate a controllability condition with multiple distributed RVMs and show that even if multiple, their structures turn out similar to [2] composed with a single quadrotor. We also elucidate the optimal placement of the RVM via the usage of controllability gramian which is not even alluded in [2] and established for the first time here. Experiments are performed to demonstrate the effectiveness of the proposed theory.

In this paper, we propose a novel sim-to-real framework to solve bolting tasks with tight tolerance and complex contact geometry which are hard to be modeled. The sim-to-real has desirable features in terms of cost and safety, however, that of the assembly task is rare due to the lack of simulator, which can robustly render multi-contact assembly. We implement the sim-to-real transfer of nut tightening policy which is adaptive to uncertain bolt positions. This can be realized through developing a novel contact model, which is fast and robust to complex assembly geometry, and novel hierarchical controller with reinforcement learning (RL), which can perform the tasks with a narrow and complicated path. The fast and robust contact model is achieved by utilizing configuration space abstraction and passive midpoint integrator (PMI), which render the simulator robust even in a high stiffness contact condition. And we use sampling-based motion planning to construct a path library and design linear quadratic tracking controller as a low-level controller to be compliant and avoid local optima. Additionally, we use the RL agent as a high-level controller to make it possible to adapt to the bolt position uncertainty, thereby realizing sim-to-real. Experiments are performed to verify our proposed sim-to-real framework.

Electrical motor and hydraulic actuation widely-used in robotics are “internal actuation” with their actuators sitting at the joint between two links. This internal actuation is fundamentally limiting to construct a large-size dexterously-articulated robot, since any external force (and its own link weight) is to be accumulated to the base multiplied by the moment arm length, requiring extremely strong/sturdy base actuator/structure as the system size increases. In this paper, we propose a novel robotic system, LASDRA (large-size aerial skeleton with distributed rotor actuation), which, by utilizing distributed rotors as “external actuation”, can overcome this limitation of internal actuation and enables us to realize large-size dexterously-articulated robots. We present its design and modeling, joint locking strategy to increase its loading capability, and also a novel decentralized control scheme to allow for compliant operation with scalability against the number of links. Trajectory tracking and valve turning experiments are also performed to validate the theory.

The MAGMaS (Multiple Aerial-Ground Manipulator System) was proposed in [1] as a heterogeneous system composed of multiple ground (mobile) manipulators and aerial robots to collaboratively manipulate a long/large-sized object and demonstrated therein for rigid load manipulation. Here, we extend this result of [1] to the case of load manipulation with flexibility, which is crucial for long/slender object manipulation, yet, not considered in [1]. We first provide a rigorous modeling of the load flexibility and its effects on the MAGMaS dynamics. We then propose a novel collaborative control framework for flexible load-tip pose tracking, where the ground manipulator provides slower nominal pose tracking with overall load weight holding, whereas the aerial robot allows for faster vibration suppression with some load weight sharing. We also discuss the issue of controllability stemming from that the aerial robot provides less number of actuation than the modes of the load flexibility; and elucidate some peculiar conditions for this vibration suppression controllability. Simulations are also performed to demonstrate the effectiveness of the proposed theory.

We propose an hierarchical control framework for multiple cooperative quadrotor-manipulator systems, which allows us to endow the common grasped object with a user-specified desired behavior (e.g., trajectory tracking, compliant interaction, etc.). To achieve this, our control framework consists of the following hierarchical layers: 1) object desired behavior design; 2) optimal cooperative force distribution; and 3) individual quadrotor-manipulator control based on object stiffness model, which can also take into account different dynamics characteristics of the (slower/coarse) quadrotor-platform and the (faster/fine) manipulator. Simulations of object transport and compliant interaction with three quadrotor-manipulator systems are performed to illustrate the theory.

We show that the Lagrange dynamics of quadrotor-manipulator systems can be completely decoupled into: 1) the center-of-mass dynamics in E(3), which, similar to the standard quadrotor dynamics, is point-mass dynamics with under-actuation and gravity effect; and 2) the “internal rotational” dynamics of the quadrotor's rotation and manipulator configuration, which assumes the form of standard Lagrange dynamics of robotic manipulator with full-actuation and no gravity effect. Relying on this structure, we propose a novel backstepping-like end-effector tracking control law, which can allow us to assign different roles for the center-of-mass control and for the internal rotational dynamics control according to task objectives. Simulations using a planar quadrotor with a 2-DOF arm are also performed to show the theory.

We present a novel cooperative grasping control framework for multiple kinematic nonholonomic mobile manipulators, which enables them to drive the grasped object with velocity commands, while rigidly maintaining the grasping shape with no dedicated grasp-enforcing fixtures and also avoiding obstacles either via their whole formation maneuver or internal formation reconfiguration. For this, nonholonomic passive decomposition [1], [2] is utilized to split the robots' motion into the three aspects (i.e., grasping shape; grasped object maneuver; internal motions) so that we can control these aspects simultaneously and separately. Peculiar dynamics of the internal motions is exploited to achieve obstacle avoidance via the formation reconfiguration. Simulations are performed to support the theory.