No abstract

In this work, we present an approach for realizing the torque control for a parallel-actuated robotic system by mapping the motion of a linear series elastic actuator (LSEA) to its driven robot joint. In most standard robotic modeling and control strategies, a robot is assumed to be actuated by torques applied directly at each joint and constructed as an open kinematic chain. However, the use of non-direct-drive actuators can violate these assumptions, causing additional challenges for the modelling and control of the robot. On our humanoid robot we use standard high level controllers to command desired joint positions and torques in order to generate desired behaviors. However, the humanoid robot is actually actuated by LSEAs, which are defined by actuator length and force. Overcoming this difference requires a method of mapping the motion and effort of an LSEA onto the corresponding joint of a robot. Our mapping approach allows for the conversion of generic desired joint position and torque trajectories consistent with standard controllers into actuator length and force trajectories that can be implemented on an LSEA-actuated robot. We present a two-stage methodology to achieve low-level torque control on our humanoid robot: a validation of the force-torque mapping in simulation, and a force controller implementation for tracking these resulting torque trajectories on a sample simulation of a single robot joint.

In this work, a generalized low-level controller is presented for sensor collection, motor input, and networking with a high-level controller. In hierarchically controlled exoskeletal systems, which utilize series elastic actuators (SEAs), the hardware for sensor collection and motor command is separated from the computationally expensive high-level controller algorithm. The low-level controller is a hardware device that must collect sensor feedback, condition and filter the measurements, send actuator inputs, and network with the high-level controller at a real-time rate. This research outlines the hardware of two printed circuit board (PCB) designs for collecting and conditioning sensor feedback from two SEA subsystems and an inertial measurement unit (IMU). The SEAs have a joint and motor encoder, motor current, and force sensor feedback that can be measured using the proposed generalized low-level controller presented in this work. In addition, the high and low-level networking approach is discussed in detail, with a full breakdown of the data storage within a communication frame during the run-time operation. The challenges of device synchronization and updates rates of high and low-level controllers are also discussed. Further, the low-level controller was validated using a pendulum test bed, complete with full sensor feedback, including IMU results for two open-loop scenarios. Moreover, this work can be extended to other hierarchically controlled robotic systems that utilize SEA subsystems, such as humanoid robots, assistive rehabilitation robots, training simulators, and robotic-assisted surgical devices. The hardware and software designs presented in this work are available open source to enable researchers with a direct solution for data acquisition and the control of low-level devices in a robotic system.

In this work, the low-level (LL) hardware for sensor collection, motor input, and networking with a high-level (HL) controller is presented for robot systems which utilize linear series elastic actuators (LSEAs) for joint actuation. In multi-joint robotic systems, LL controllers rely on sensor readings to control each joint and communicate the obtained information to the HL controller. This research outlines the hardware design of two printed circuit boards (PCBs), as well as the use of an EasyCAT PRO board for communication. An in-house sensor interface shield is designed as an extension of the TM4C123GXL TIVA microcontroller launchpad and another in-house shield connects to the AZBDC12A8 analog servo drive, or rather, the motor controller. These PCBs allow for sensor integration with circuits that route, filter, or manipulate data obtained from the sensors. The goal of the sensor interface shield is to interface between sensors and the microcontroller. The sensor board takes readings from a force sensor, absolute encoder, quadrature encoder, as well as adjusting the pulse-width modulation (PWM) signal that is sent to the motors. The main purpose of the motor shield is to supply power, route the PWM input, and filter the current output of the motor. The final designs for both the shields are built in the PCB design software Eagle. Overall, these boards will allow for better sensor integration for LL controllers which interface with LSEA driven multi-joint robotic systems.

In this work, a low-level software framework is proposed to simplify software development for Hardware Abstract Layered (HAL) control systems, identify networking methods for accurate real-time communication between devices, and verify task completion. The framework is implemented on a distributed microcontroller system composed of Texas Instruments TM4C123GXL Tivas for a multi-joint robot. The robot’s high-level controller executes dynamic motion control algorithms, with low-level controllers responsible for each individual joint. All microcontroller software is unified into one program and uses initialization files from the high-level controller to configure each individual Tiva depending on its location on the robot. The EtherCAT communication protocol is utilized to avoid unnecessary overhead from traditional networking protocols. A real-time operating system, TI-RTOS, enforces crucial deadlines and provides powerful diagnostic tools for the designer to optimize task completion. Overall, our proposed framework overcomes the major challenges of writing low-level control software so that development is less time-consuming, simpler to manage, and easier to validate. Further, this work can be used for many kinds of robotic systems and applications that use microcontrollers within a multi-layered control architecture.