Talk 1 : Novel instrument for kinematic measurements of mild traumatic brain injury
Speaker : Fidel Hernandez
Abstract:
Mild traumatic brain injuries (mTBI) from repeated head collisions have been linked to neurodegeneration in athletes and soldiers. Human injury tolerance is complex and poorly understood, making identification and prevention ineffective. Using a novel instrumented mouthguard, we measured human skull kinematics during head collisions, including the first complete six degree of freedom measurements of injury. We show that classical injury criteria could not describe the wide spatiotemporal variability of head collision biomechanics. Injury tolerance appears to vary by direction, as a weighted multidimensional classifier was required to unambiguously identify injury. Finite element simulations predicted tissue deformations in the corpus callosum and brainstem consistent with observed cognitive impairment and loss of consciousness. Our findings support the use of high-dimensional measurement devices as clinically translatable means of real time injury identification to prevent repeat trauma and neurodegeneration.


Talk 2 : Opposed Grip Mechanisms for Inverted Perching
Speaker : Morgan Pope
Abstract:
Dry adhesives are attractive for perching applications due to their extremely fast passive response times and ease of detachment.  In order to generate adhesion, the proper ratio of shear/normal force must be maintained, which leads to the opposed grip design which uses internal force to enable inverted attachment.


Talk 3 : Robust and Flexible Control of Muscle-Driven Simulation
Speaker : Justin Si
Abstract:
We have been developing a controller to drive human musculoskeletal models to track experimental data with minimum effort. The desired properties of this new controller include robustness, flexibility, efficiency, generalizability as well as optimality. I will briefly describe our problem formulation and the methods we have tried to solve it. I will also show some experiment results and talk about the existing challenges.


Talk 4 : Contact Event Detection for Robotic Drilling
Speaker : Alice Wu
Abstract:
To ensure safe and reliable operation in a robotic oil drilling system, it is essential to detect contact events such as impacts and slips between end-effectors and workpieces. In this challenging application, where high forces are used to manipulate heavy metal pipes in noisy environments, acoustic emissions (AE) sensors offer a promising contact sensing solution. Realtime AE signal features are used to create a multinomial contact event classifier. The sensitivity of signal features to a variety of contact events including two types of slip is presented. Results indicate that the classifier is able to robustly and dynamically classify contact events with >90% accuracy using a small set of AE signal features.


Talk 5 : Learning complex neural network policies with trajectory optimization
Speaker : Sergey Levine
Abstract:
Reinforcement learning by means of policy search offers the promise of automatically learning control policies for complex tasks in noisy or partially observed environments. However, successful application of policy search typically requires designing a low-dimensional, compact representation of the policy that can be efficiently optimized with current methods. Unfortunately, much of the intelligence of the controller is often contained in this representation, rather than in the learned parameters. In this talk, I will describe my recent work on guided policy search algorithms, which use trajectory optimization to guide the policy search into regions of high reward and allow much more complex policies to be learned. Guided policy search can be used to learn general-purpose neural network controllers for tasks such as locomotion without manual engineering of the controller representation. I will present recent results for learning policies for simulated bipedal locomotion and push recovery, and discuss some ongoing work on a new version of the guided policy search algorithm that does not require a model of the system dynamics.