scholarly journals Performance During Whole Body Reaching Movements Is Impaired In Hypergravity While Preserved In Microgravity

2021 ◽  
Author(s):  
Loic Chomienne ◽  
Patrick Sainton ◽  
Fabrice R Sarlegna ◽  
Lionel Bringoux
Keyword(s):  
Angular Displacement ◽  
Muscular Activity ◽  
Movement Planning ◽  
Reaching Movements ◽  
Whole Body ◽  
Emg Activity ◽  
Initial State ◽  
Planning And Control ◽  
And Control ◽  
Muscular Activation

While recent findings demonstrated the importance of initial state estimates about gravity for optimized motor control, it remains unclear whether novel initial states are rapidly implemented movement planning (and control) in the same way when gravity is removed or increased. Here, we investigated the effect of microgravity and hypergravity exposure on whole-body reaching movements performed by standing subjects during parabolic flights. Reaching movements were analyzed regarding spatial accuracy (finger endpoint deviation), arm kinematics (arm angular displacement), whole-body kinematics (body bending) and EMG activity (muscular activation and synergies) of eight muscles. Results showed that kinematics and muscular activity are adjusted in microgravity allowing accurate whole-body reaching, thus confirming the perfectly scaled sensorimotor reorganization reported in previous recent studies. Contrasting with these observations, participants hardly reached the targets in 1.8g (systematic undershot). Strikingly, whole-body kinematics remained unchanged in hypergravity compared to 1g observations. Finally, while the analysis of synergies highlighted a comparable muscular organization in all gravitational contexts, our main findings revealed local muscular adjustments leading to accurate motor responses in microgravity, but not in hypergravity.

Whole-body adaptation to novel dynamics does not transfer between effectors

2021 ◽  
Author(s):  
Alison Pienciak-Siewert ◽  
Alaa A Ahmed
Keyword(s):  
Postural Control ◽  
Arm Movement ◽  
Movement Planning ◽  
Reaching Movements ◽  
Whole Body ◽  
Postural Control System ◽  
Movement Dynamics ◽  
Gradual Introduction ◽  
Postural Movement ◽  
The Brain

How does the brain coordinate concurrent adaptation of arm movements and standing posture? From previous studies, the postural control system can use information about previously adapted arm movement dynamics to plan appropriate postural control; however, it is unclear whether postural control can be adapted and controlled independently of arm control. The present study addresses that question. Subjects practiced planar reaching movements while standing and grasping the handle of a robotic arm, which generated a force field to create novel perturbations. Subjects were divided into two groups, for which perturbations were introduced in either an abrupt or gradual manner. All subjects adapted to the perturbations while reaching with their dominant (right) arm, then switched to reaching with their non-dominant (left) arm. Previous studies of seated reaching movements showed that abrupt perturbation introduction led to transfer of learning between arms, but gradual introduction did not. Interestingly, in this study neither group showed evidence of transferring adapted control of arm or posture between arms. These results suggest primarily that adapted postural control cannot be transferred independently of arm control in this task paradigm. In other words, whole-body postural movement planning related to a concurrent arm task is dependent on information about arm dynamics. Finally, we found that subjects were able to adapt to the gradual perturbation while experiencing very small errors, suggesting that both error size and consistency play a role in driving motor adaptation.

scholarly journals Parareal with a learned coarse model for robotic manipulation

2020 ◽  
Vol 23 (1-4) ◽  
Author(s):  
Wisdom Agboh ◽  
Oliver Grainger ◽  
Daniel Ruprecht ◽  
Mehmet Dogar
Keyword(s):  
Time Integration ◽  
Robotic Manipulation ◽  
Multiple Objects ◽  
Initial State ◽  
Link Type ◽  
Planning And Control ◽  
Physics Model ◽  
Coarse Model ◽  
Computational Bottleneck ◽  
And Control

AbstractA key component of many robotics model-based planning and control algorithms is physics predictions, that is, forecasting a sequence of states given an initial state and a sequence of controls. This process is slow and a major computational bottleneck for robotics planning algorithms. Parallel-in-time integration methods can help to leverage parallel computing to accelerate physics predictions and thus planning. The Parareal algorithm iterates between a coarse serial integrator and a fine parallel integrator. A key challenge is to devise a coarse model that is computationally cheap but accurate enough for Parareal to converge quickly. Here, we investigate the use of a deep neural network physics model as a coarse model for Parareal in the context of robotic manipulation. In simulated experiments using the physics engine Mujoco as fine propagator we show that the learned coarse model leads to faster Parareal convergence than a coarse physics-based model. We further show that the learned coarse model allows to apply Parareal to scenarios with multiple objects, where the physics-based coarse model is not applicable. Finally, we conduct experiments on a real robot and show that Parareal predictions are close to real-world physics predictions for robotic pushing of multiple objects. Code (https://doi.org/10.5281/zenodo.3779085) and videos (https://youtu.be/wCh2o1rf-gA) are publicly available.

Movement Behavior for Soldier Agents on a Virtual Battlefield

2003 ◽  
Vol 12 (4) ◽  
pp. 387-410 ◽  
Author(s):  
Douglas A. Reece
Keyword(s):  
Search Algorithm ◽  
Human Movement ◽  
Movement Planning ◽  
Movement Behavior ◽  
Behavior Model ◽  
Topological Map ◽  
Hybrid Search ◽  
Individual Agent ◽  
Planning And Control ◽  
And Control

We have developed a movement behavior model for soldier agents who populate a virtual battlefield environment. Whereas many simulations have addressed human movement behavior before, none of them has comprehensively addressed realistic military movement at individual and unit levels. To design an appropriate movement behavior model, we found it necessary to elaborate all of the requirements on movement from the military tasks of interest, define a behavior architecture that encompasses all required movement tasks, select appropriate movement planning and control approaches in light of the requirements, and implement the planning and control algorithms with novel enhancements to achieve satisfactory results. The breadth of requirements in this problem domain makes simple behavior architectures inadequate and prevents any single planning approach from easily accomplishing all tasks. In our behavior architecture, a hierarchy of tasks is distributed over unit leaders and unit members. For movement planning, we use an A* search algorithm on a hybrid search space comprising a two-dimensional regular grid and a topological map; the plan produced is a series of waypoints annotated with posture and speed changes. Individuals control movement with reactive steering behaviors. The result is a system that can realistically plan and execute a variety of unit and individual agent movement tasks on a virtual battlefield.

scholarly journals Versatile Locomotion Planning and Control for Humanoid Robots

2021 ◽  
Vol 8 ◽  
Author(s):  
Junhyeok Ahn ◽  
Steven Jens Jorgensen ◽  
Seung Hyeon Bang ◽  
Luis Sentis
Keyword(s):  
Trajectory Optimization ◽  
Control Method ◽  
Biped Robot ◽  
Humanoid Robots ◽  
Integer Program ◽  
Whole Body ◽  
Walking Robots ◽  
Planning And Control ◽  
Floating Base ◽  
And Control

We propose a locomotion framework for bipedal robots consisting of a new motion planning method, dubbed trajectory optimization for walking robots plus (TOWR+), and a new whole-body control method, dubbed implicit hierarchical whole-body controller (IHWBC). For versatility, we consider the use of a composite rigid body (CRB) model to optimize the robot’s walking behavior. The proposed CRB model considers the floating base dynamics while accounting for the effects of the heavy distal mass of humanoids using a pre-trained centroidal inertia network. TOWR+ leverages the phase-based parameterization of its precursor, TOWR, and optimizes for base and end-effectors motions, feet contact wrenches, as well as contact timing and locations without the need to solve a complementary problem or integer program. The use of IHWBC enforces unilateral contact constraints (i.e., non-slip and non-penetration constraints) and a task hierarchy through the cost function, relaxing contact constraints and providing an implicit hierarchy between tasks. This controller provides additional flexibility and smooth task and contact transitions as applied to our 10 degree-of-freedom, line-feet biped robot DRACO. In addition, we introduce a new open-source and light-weight software architecture, dubbed planning and control (PnC), that implements and combines TOWR+ and IHWBC. PnC provides modularity, versatility, and scalability so that the provided modules can be interchanged with other motion planners and whole-body controllers and tested in an end-to-end manner. In the experimental section, we first analyze the performance of TOWR+ using various bipeds. We then demonstrate balancing behaviors on the DRACO hardware using the proposed IHWBC method. Finally, we integrate TOWR+ and IHWBC and demonstrate step-and-stop behaviors on the DRACO hardware.

scholarly journals System theoretic approach to sustainable development problems

2011 ◽  
Vol 21 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Vladan Batanovic ◽  
Slobodan Guberinic ◽  
Radivoj Petrovic
Keyword(s):  
Sustainable Development ◽  
State Space ◽  
Operations Research ◽  
The State ◽  
Feasible Region ◽  
Theoretic Approach ◽  
Initial State ◽  
The Sustainable Development ◽  
Planning And Control ◽  
And Control

This paper shows that the concepts and methodology contained in the system theory and operations research are suitable for application in the planning and control of the sustainable development. The sustainable development problems can be represented using the state space concepts, such as the transition of system, from the given initial state to the final state. It is shown that sustainable development represents a specific control problem. The peculiarity of the sustainable development is that the target is to keep the system in the prescribed feasible region of the state space. The analysis of planning and control problems of sustainable development has also shown that methods developed in the operations research area, such as multicriteria optimization, dynamic processes simulation, non-conventional treatment of uncertainty etc. are adequate, exact base, suitable for resolution of these problems.

Eye Movements When Observing Predictable and Unpredictable Actions

2006 ◽  
Vol 96 (3) ◽  
pp. 1358-1369 ◽  
Author(s):  
Gerben Rotman ◽  
Nikolaus F. Troje ◽  
Roland S. Johansson ◽  
J. Randall Flanagan
Keyword(s):  
Eye Movements ◽  
Hand Movement ◽  
Landing Site ◽  
Movement Planning ◽  
Gaze Behavior ◽  
Direct Gaze ◽  
Planning And Control ◽  
Landing Sites ◽  
Target Block ◽  
And Control

We previously showed that, when observers watch an actor performing a predictable block-stacking task, the coordination between the observer's gaze and the actor's hand is similar to the coordination between the actor's gaze and hand. Both the observer and the actor direct gaze to forthcoming grasp and block landing sites and shift their gaze to the next grasp or landing site at around the time the hand contacts the block or the block contacts the landing site. Here we compare observers' gaze behavior in a block manipulation task when the observers did and when they did not know, in advance, which of two blocks the actor would pick up first. In both cases, observers managed to fixate the target ahead of the actor's hand and showed proactive gaze behavior. However, these target fixations occurred later, relative to the actor's movement, when observers did not know the target block in advance. In perceptual tests, in which observers watched animations of the actor reaching partway to the target and had to guess which block was the target, we found that the time at which observers were able to correctly do so was very similar to the time at which they would make saccades to the target block. Overall, our results indicate that observers use gaze in a fashion that is appropriate for hand movement planning and control. This in turn suggests that they implement representations of the manual actions required in the task and representations that direct task-specific eye movements.

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