Co-exploring Actuator Antagonism and Bio-inspired Control in a Printable Robot Arm

The human arm is capable of performing fast targeted movements with high precision, say in pointing with a mouse cursor, but is inherently ‘soft’ due to the muscles, tendons and other tissues of which it is composed. Robot arms are also becoming softer, to enable robustness when operating in real-world environments, and to make them safer to use around people. But softness comes at a price, typically an increase in the complexity of the control required for a given task speed/accuracy requirement. Here we explore how fast and precise joint movements can be simply and effectively performed in a soft robot arm, by taking inspiration from the human arm. First, viscoelastic actuator-tendon systems in an agonist-antagonist setup provide joints with inherent damping, and stiffness that can be varied in real-time through co-contraction. Second, a light-weight and learnable inverse model for each joint enables a fast ballistic phase that drives the arm close to a desired equilibrium point and co-contraction tuple, while the final adjustment is done by a feedback controller. The approach is embodied in the GummiArm, a robot which can almost entirely be printed on hobby-grade 3D printers. This enables rapid and iterative co-exploration of ‘brain’ and ‘body’, and provides a great platform for developing adaptive and bio-inspired behaviours

Soft robotic snake with variable stiffness actuation

© Springer International Publishing AG 2017. In this paper, we present a prototype of a 3D printed snake-like robot for search and rescue applications, inspired by biological snake anatomy and locomotion. Unlike traditional robotics, this design takes advantage of soft materials to create a robot that is resilient to shock impacts, such as from falling debris or unsound flooring, and that can very its stiffness. The robot uses a flexible spine to connect multiple sections, allowing controlled actuation while providing a sturdy structure. Variable stiffness actuation is implemented through the use of elastic materials to act as tendons for the body, in an agonist-antagonist setup. Actuation occurs through the use of Robotis Dynamixel AX-12A servos, controlled by a Trossen Robotics Arbotix-M Robocon-troller. The design features a head, containing a Raspberry Pi 3 and a Pi Camera Module. This added embedded computation can connect to a remote PC via wireless communication, allowing an operator to control the robot. This paper discusses the design and early stage testing for the prototype, and shows that robots based on soft 3D printed materials and mechanisms are viable, and effective

Graceful degradation under noise on brain inspired robot controllers

How can we build robot controllers that are able to work under harsh conditions, but without experiencing catastrophic failures? As seen on the recent Fukushima’s nuclear disaster, standard robots break down when exposed to high radiation environments. Here we present the results from two arrangements of Spiking Neural Networks, based on the Liquid State Machine (LSM) framework, that were able to gracefully degrade under the effects of a noisy current injected directly into each simulated neuron. These noisy currents could be seen, in a simplified way, as the consequences of exposition to non-destructive radiation. The results show that not only can the systems withstand noise, but one of the configurations, the Modular Parallel LSM, actually improved its results, in a certain range, when the noise levels were increased. Also, the robot controllers implemented in this work are suitable to run on a modern, power efficient neuromorphic hardware such as SpiNNaker

An Open-Source Social Robot Based on Compliant Soft Robotics for Therapy with Children with ASD

Therapy with robotic tools is a promising way to help improve verbal and nonverbal communication in children. The robotic tools are able to increase aspects such as eye contact and the ability to follow instructions and to empathize with others. This work presents the design methodology, development, and experimental validation of a novel social robot based on CompliAnt SofT Robotics called the CASTOR robot, which intends to be used as an open-source platform for the long-term therapy of children with autism spectrum disorder (CwASD). CASTOR integrates the concepts of soft actuators and compliant mechanisms to create a replicable robotic platform aimed at real therapy scenarios involving physical interaction between the children and the robot. The validation shows promising results in terms of robustness and the safety of the user and robot. Likewise, mechanical tests assess the robot’s response to blocking conditions for two critical modules (i.e., neck and arm) in interaction scenarios. Future works should focus on the validation of the robot’s effectiveness in the therapy of CwASD.</jats:p

Proof-of-concept modular robot platform for cauliflower harvesting

This paper presents a proof-of-concept platform for demonstrating robotic harvesting of summer-varieties of cauliflower, and early tests performed under laboratory conditions. The platform is designed to be modular and has two dexterous robotic arms with variable-stiffness technology. The bi-manual configuration enables the separation of grasping and cutting behaviours into separate robot manipulators. By exploiting the passive compliance of the variable-stiffness arms, the system can operate with both grasping and cutting tool close to the ground. Multiple 3D vision cameras are used to track the cauliflowers in real-time, and to attempt to assess the maturity. Early experiments with the platform in the laboratory highlight the potential and challenges of the platform

Active stereo platform: online epipolar geometry update

This paper presents a novel method to update a variable epipolar geometry platform directly from the motor encoder based on mapping the motor encoder angle to the image space angle, avoiding the use of feature detection algorithms. First, an offline calibration is performed to establish a relationship between the image space and the hardware space. Second, a transformation matrix is generated using the results from this mapping. The transformation matrix uses the updated epipolar geometry of the platform to rectify the images for further processing. The system has an overall error in the projection of ± 5 pixels, which drops to ± 1.24 pixels when the verge angle increases beyond 10°. The platform used in this project has 3° of freedom to control the verge angle and the size of the baseline