Using Asymmetry to Your Advantage: Learning to Acquire and Accept External Assistance During Prolonged Split-belt Walking

People can learn to exploit external assistance during walking to reduce energetic cost. For example, walking on a split-belt treadmill affords the opportunity for people to redistribute the mechanical work performed by the legs to gain assistance from the difference in belts’ speed and reduce energetic cost. Though we know what people should do to acquire this assistance, this strategy is not observed during typical adaptation studies. We hypothesized that extending the time allotted for adaptation would result in participants adopting asymmetric step lengths to increase the assistance they can acquire from the treadmill. Here, participants walked on a split-belt treadmill for 45 min while we measured spatiotemporal gait variables, metabolic cost, and mechanical work. We show that when people are given sufficient time to adapt, they naturally learn to step further forward on the fast belt, acquire positive mechanical work from the treadmill, and reduce the positive work performed by the legs. We also show that spatiotemporal adaptation and energy optimization operate over different timescales: people continue to reduce energetic cost even after spatiotemporal changes have plateaued. Our findings support the idea that walking with symmetric step lengths, which is traditionally thought of as the endpoint of adaptation, is only a point in the process by which people learn to take advantage of the assistance provided by the treadmill. These results provide further evidence that reducing energetic cost is central in shaping adaptive locomotion, but this process occurs over more extended timescales than those used in typical studies

General Variability Leads to Specific Adaptation Toward Energy Optimal Policies

Our nervous systems can learn optimal control policies in response to changes to our bodies, tasks, and movement contexts. For example, humans can learn to adapt their control policy in walking contexts where the energy-optimal policy is shifted along variables such as step frequency or step width. However, it is unclear how the nervous system determines which ways to adapt its control policy. Here, we asked how human participants explore through variations in their control policy to identify more optimal policies in new contexts. We created new contexts using exoskeletons that apply assistive torques to each ankle at each walking step. We analyzed four variables that spanned the levels of the whole movement, the joint, and the muscle: step frequency, ankle angle range, total soleus activity, and total medial gastrocnemius activity. We found that, across all of these analyzed variables, variability increased upon initial exposure to new contexts and then decreased with experience. This led to adaptive changes in the magnitude of specific variables, and these changes were correlated with reduced energetic cost. The timescales by which adaptive changes progressed and variability decreased were faster for some variables than others, suggesting a reduced search space within which the nervous system continues to optimize its policy. These collective findings support the principle that exploration through general variability leads to specific adaptation toward optimal movement policies

An Overview on Principles for Energy Efficient Robot Locomotion.

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied