We propose a novel high-force/high-precision interaction control framework of a dual-arm robot system on a flexible base, with one arm holding, or making contact with, a supporting surface, while the other arm can exert any arbitrary wrench in a certain polytope through a desired pose against environments or objects. Our proposed framework can achieve high-force/precision tasks by utilizing the supporting surface just as we humans do while taking into account various important constraints (e.g., system stability, joint angle/torque limits, friction-cone constraint, etc.) and the passive compliance of the flexible base. We first design the control as a combination of: 1) nominal control; 2) active stiffness control; and 3) feedback wrench control. We then sequentially perform optimizations of the nominal configuration (and its related wrenches) and the active stiffness control gain. We also design the proportional–integral type feedback wrench control to improve the robustness and precision of the control. The key theoretical enabler for our framework is a novel stiffness analysis of the dual-arm system with flexibility, which, when combined with certain constraints, provides some peculiar relations, that can effectively be used to significantly simplify the optimization problem-solving and to facilitate the feedback wrench control design by manifesting the compliance relation at the interaction port. The efficacy of the theory is then validated and demonstrated through simulations and experiments.

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.

Robots have taken the place of human operators in hazardous and challenging jobs requiring high dexterity in manipulation, and robots with skin for force and tactile sensing that mimics the function of mechanoreception in animals will be highly dexterous in performing complex tasks. In this study, we propose the design of modular robotic skin, capable of detecting the magnitude and the location of a contact force simultaneously. Each skin module needs three degrees of freedom in sensing in order to estimate the horizontal and the vertical locations of the contact force as well as its magnitude. Force sensing in the proposed skin is enabled by a custom-designed triangular beam structure underneath the skin cover. A force applied to the skin cover causes the bending of the beam, which is detected by fiber optic strain sensors. The result shows the resolutions of 1.45 N for force estimation and 1.85 mm and 1.91 mm for contact localization in horizontal and vertical directions, respectively. We also demonstrate how the proposed skin can be used for remote and autonomous control of commercial robotic arms equipped with an array of the skin modules.

This paper proposes an external wrench estimation method for modular manipulators, where each link module is driven with external actuation (e.g., rotors, thrusters) and inter-module joints can be locked to increase end-effector stiffness or workforce of the manipulator. For such systems, the commonly-used momentum-based observer (MBO [1]) is not suitable due to the presence of unknown joint locking (JL) torque and also the degeneracy of Jacobian transpose relation with the system degree-of-freedom (DOF) becoming less than six with the joint locking. To overcome this, we propose two novel external wrench estimation algorithms: a distributed algorithm based on recursive Newton-Euler dynamics and a centralized algorithm based on D'Alembert's principle, both using an F/T (force/torque) sensor at the base. Experiments are conducted to demonstrate the effectiveness of the proposed algorithms.

We propose a novel model-free optimal estimation and sensor placement framework for a high-DOF (degree-of-freedom) EKC (elastic kinematic chain) with only a limited number of IMU (inertial measurement unit) sensors based on POD (proper orthogonal decomposition) and MAP (maximum a posteriori) estimation. First, we (off-line) excite the system richly enough, collect the data and perform the POD to extract dominant and non-dominant modes. We then decide the minimum number of IMUs according to the dominant modes, and construct the prior distribution of the output (i.e., top-end position of EKC) based on the singular value of each POD mode. We also formulate the MAP estimation given the prior distribution and different placements of the IMUs and choose the optimal IMU placement to maximize the posterior probability. This optimal placement is then used for real-time output estimation of the EKC. Experiments are also performed to verify the theory.

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.