Human Stiffness Perception and Learning in Interacting With Compliant Environments.

Humans are capable of adjusting their posture stably when interacting with a compliant surface. Their whole-body motion can be modulated in order to respond to the environment and reach to a stable state. In perceiving an uncertain external force, humans repetitively push it and learn how to produce a stable state.

Exploiting Spherical Projections To Generate Human-Like Wrist Pointing Movements.

The mechanism behind the generation of human movements is of great interest in many fields (e.g. robotics and neuroscience) to improve therapies and technologies.

HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems.

Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the force feedback from their proprioception. However, this ability is extremely challenging to reproduce in robots, especially when dealing with complex interaction dynamics, distributed contacts, and contact switching. Current model-based controllers require accurate interaction modelling to account for contacts and stabilise the interaction.

An Optimization-Based Locomotion Controller for Quadruped Robots Leveraging Cartesian Impedance Control.

Quadruped robots require compliance to handle unexpected external forces, such as impulsive contact forces from rough terrain, or from physical human-robot interaction. This paper presents a locomotion controller using Cartesian impedance control to coordinate tracking performance and desired compliance, along with Quadratic Programming (QP) to satisfy friction cone constraints, unilateral constraints, and torque limits. First, we resort to projected inverse-dynamics to derive an analytical control law of Cartesian impedance control for constrained and underactuated systems (typically a quadruped robot).

Analytic Model for Quadruped Locomotion Task-Space Planning.

Despite the extensive presence of the legged locomotion in animals, it is extremely challenging to be reproduced with robots. Legged locomotion is an dynamic task which benefits from a planning that takes advantage of the gravitational pull on the system. However, the computational cost of such optimization rapidly increases with the complexity of kinematic structures, rendering impossible real-time deployment in unstructured environments.

Co-ordination of the upper and lower limbs for vestibular control of balance.

Key Points: When standing and holding an earth-fixed object, galvanic vestibular stimulation (GVS) can evoke upper limb responses to maintain balance. In the present study, we determined how these responses are affected by grip context (no contact, light grip and firm grip), as well as how they are co-ordinated with the lower limbs to maintain balance. When GVS was applied during firm grip, hand and ground reaction forces were generated.

Optimal control of reaching includes kinematic constraints.

We investigate adaptation under a reaching task with an acceleration-based force field perturbation designed to alter the nominal straight hand trajectory in a potentially benign manner: pushing the hand off course in one direction before subsequently restoring towards the target. In this particular task, an explicit strategy to reduce motor effort requires a distinct deviation from the nominal rectilinear hand trajectory. Rather, our results display a clear directional preference during learning, as subjects adapted perturbed curved trajectories towards their initial baselines.