IPAB Workshop-13/01/2022

Daniel Gordon Title: Human-in-the-loop Optimisation of Exoskeleton Assistance via Online Simulation of Metabolic Cost Abstract: Many assistive robotic devices have been developed to augment or assist human locomotion. Despite advancements in design and control algorithms, this task remains challenging. Human walking strategies are unique and complex, and assistance strategies based on the dynamics of unassisted locomotion typically offer only modest reductions to the metabolic cost of walking. Recently, human-in-the-loop (HIL) methodologies have been used to identify subject-specific assistive strategies which offer significant improvements to energy savings. However, current implementations suffer from long measurement times, necessitating the use of low-dimensional control parameterisations, and possibly requiring multi-day collection protocols to avoid subject fatigue. We present a HIL methodology which optimises the assistive torques provided by a powered hip exoskeleton. Using musculoskeletal modelling, we are able to evaluate simulated metabolic rate online. We applied our methodology!   to identify assistive torque profiles for 7 subjects walking on a treadmill, and found greater reductions to metabolic cost when compared to generic or off-the-shelf controllers. The time investment required to identify assistance strategies via our protocol is significantly lower when compared to existing protocols relying on calorimetry. In the future, frameworks such as these could be used to enable shorter HIL protocols or exploit more complex control parameterisations for greater energy savings. Theodoros Stouraitis Title: Manipulation with Switching Contacts for Dyadic Human-Robot Collaboration Abstract: In this talk, we will consider manipulation and co-manipulation tasks which require making and breaking of contacts with the object of interest. With these tasks will investigate problems that involve long horizon planning in hybrid domains (both continuous and discrete variables), online adaptation of hybrid motion plans and transitions from free motion to contact in high speeds. To address these problems, we propose Trajectory Optimization method based on an event-driven hybrid motion planning formulation along with its extensions. Key concepts of our approach include the efficient combination of TO methods with informed search methods for online re-planning and the incorporation of an explicit contact force transmission model to generate impact-aware motion plans. To illustrate the capabilities of our methods, we present evaluations in physical simulations as well as experimental validations with single-arm and dual-arm robots co-manipulating and receiving objects.