Data-driven robotic manipulation of cloth-like deformable objects : the present, challenges and future prospects

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level of compression strength while two points on the article are pushed towards each other and include objects such as ropes (1D), fabrics (2D) and bags (3D). In general, CDOs’ many degrees of freedom (DoF) introduce severe self-occlusion and complex state–action dynamics as significant obstacles to perception and manipulation systems. These challenges exacerbate existing issues of modern robotic control methods such as imitation learning (IL) and reinforcement learning (RL). This review focuses on the application details of data-driven control methods on four major task families in this domain: cloth shaping, knot tying/untying, dressing and bag manipulation. Furthermore, we identify specific inductive biases in these four domains that present challenges for more general IL and RL algorithms.Publisher PDFPeer reviewe

Physics-, social-, and capability- based reasoning for robotic manipulation

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 124-128).Robots that can function in human-centric domains have the potential to help humans with the chores of everyday life. Moreover, dexterous robots with the ability to reason about the maneuvers they execute for manipulation tasks can function more autonomously and intelligently. This thesis outlines the development of a reasoning architecture that uses physics-, social-, and agent capability-based knowledge to generate manipulation strategies that a dexterous robot can implement in the physical world. The reasoning system learns object affordances through a combination of observations from human interactions, explicit rules and constraints imposed on the system, and hardcoded physics-based logic. Observations from humans performing manipulation tasks are also used to develop a unique manipulation repertoire suitable for the robot. The system then uses Bayesian Networks to probabilistically determine the best manipulation strategies for the robot to execute on new objects. The robot leverages this knowledge during experimental trials where manipulation strategies suggested by the reasoning architecture are shown to perform well in new manipulation environments.by Kenton J. Williams.S.M

Scaled Autonomy for Networked Humanoids

Humanoid robots have been developed with the intention of aiding in environments designed for humans. As such, the control of humanoid morphology and effectiveness of human robot interaction form the two principal research issues for deploying these robots in the real world. In this thesis work, the issue of humanoid control is coupled with human robot interaction under the framework of scaled autonomy, where the human and robot exchange levels of control depending on the environment and task at hand. This scaled autonomy is approached with control algorithms for reactive stabilization of human commands and planned trajectories that encode semantically meaningful motion preferences in a sequential convex optimization framework. The control and planning algorithms have been extensively tested in the field for robustness and system verification. The RoboCup competition provides a benchmark competition for autonomous agents that are trained with a human supervisor. The kid-sized and adult-sized humanoid robots coordinate over a noisy network in a known environment with adversarial opponents, and the software and routines in this work allowed for five consecutive championships. Furthermore, the motion planning and user interfaces developed in the work have been tested in the noisy network of the DARPA Robotics Challenge (DRC) Trials and Finals in an unknown environment. Overall, the ability to extend simplified locomotion models to aid in semi-autonomous manipulation allows untrained humans to operate complex, high dimensional robots. This represents another step in the path to deploying humanoids in the real world, based on the low dimensional motion abstractions and proven performance in real world tasks like RoboCup and the DRC

Becoming Human with Humanoid

Nowadays, our expectations of robots have been significantly increases. The robot, which was initially only doing simple jobs, is now expected to be smarter and more dynamic. People want a robot that resembles a human (humanoid) has and has emotional intelligence that can perform action-reaction interactions. This book consists of two sections. The first section focuses on emotional intelligence, while the second section discusses the control of robotics. The contents of the book reveal the outcomes of research conducted by scholars in robotics fields to accommodate needs of society and industry

Sensors for Robotic Hands: A Survey of State of the Art

Recent decades have seen significant progress in the field of artificial hands. Most of the surveys, which try to capture the latest developments in this field, focused on actuation and control systems of these devices. In this paper, our goal is to provide a comprehensive survey of the sensors for artificial hands. In order to present the evolution of the field, we cover five year periods starting at the turn of the millennium. At each period, we present the robot hands with a focus on their sensor systems dividing them into categories, such as prosthetics, research devices, and industrial end-effectors.We also cover the sensors developed for robot hand usage in each era. Finally, the period between 2010 and 2015 introduces the reader to the state of the art and also hints to the future directions in the sensor development for artificial hands

Neural and motor basis of inter-individual interactions

The goal of my Ph.D. work was to investigate the behavioral markers and the brain activities responsible for the emergence of sensorimotor communication. Sensorimotor communication can be defined as a form of communication consisting into flexible exchanges based on bodily signals, in order to increase the efficiency of the inter-individual coordination. For instance, a soccer player carving his movements to inform another player about his intention. This form of interaction is highly dependent of the motor system and the ability to produce appropriate movements but also of the ability of the partner to decode these cues. To tackle these facets of human social interaction, we approached the complexity of the problem by splitting my research activities into two separate lines of research. First, we pursued the examination of motor-based humans\u2019 capability to perceive and \u201cread\u201d other\u2019s behaviors in focusing on single-subject experiment. The discovery of mirror neurons in monkey premotor cortex in the early nineties (di Pellegrino et al. 1992) motivated a number of human studies on this topic (Rizzolatti and Craighero 2004). The critical finding was that some ventral premotor neurons are engaged during visual presentation of actions performed by conspecifics. More importantly, those neurons were shown to encode also the actual execution of similar actions (i.e. irrespective of who the acting individual is). This phenomenon has been highly investigated in humans by using cortical and cortico-spinal measures (for review see, fMRI: Molenberghs, Cunnington, and Mattingley 2012; TMS: Naish et al. 2014; EEG: Pineda 2008). During single pulse TMS (over the primary motor cortex), the amplitude of motor evoked potentials (MEPs) provides an index of corticospinal recruitment. During action observation the modulation of this index follow the expected changes during action execution (Fadiga et al. 1995). However, dozens of studies have been published on this topic and revealed important inconsistencies. For instance, MEPs has been shown to be dependent on observed low-level motor features (e.g. kinematic features or electromyography temporal coupling; Gangitano, Mottaghy, and Pascual-Leone 2001; Borroni et al. 2005; Cavallo et al. 2012) as well as high level movement properties (e.g. action goals; Cattaneo et al. 2009; Cattaneo et al. 2013). Furthermore, MEPs modulations do not seem to be related to the observed effectors (Borroni and Baldissera 2008; Finisguerra et al. 2015; Senna, Bolognini, and Maravita 2014), suggesting their independence from low-level movement features. These contradictions call for new paradigms. Our starting hypothesis here is that the organization and function of the mirror mechanism should follow that of the motor system during action execution. Hence, we derived three action observation protocols from classical motor control theories: 1) The first study was motivated by the fact that motor redundancy in action execution do not allow the presence of a one-to-one mapping between (single) muscle activation and action goals. Based on that, we showed that the effect of action observation (observation of an actor performing a power versus a precision grasp) are variable at the single muscle level (MEPs; motor evoked potentials) but robust when evaluating the kinematic of TMS-evoked movements. Considering that movements are based on the coordination of multiple muscle activations (muscular synergies), MEPs may represent a partial picture of the real corticospinal activation. Inversely, movement kinematics is both the final functional byproduct of muscles coordination and the sole visual feedback that can be extracted from action observation (i.e. muscle recruitment is not visible). We conclude that TMS-evoked kinematics may be more reliable in representing the state of the motor system during action observation. 2) In the second study, we exploited the inter-subject variability inherent to everyday whole-body human actions, to evaluate the link between individual motor signatures (or motor styles) and other\u2019s action perception. We showed no group-level effect but a robust correlation between the individual motor signature recorded during action execution and the subsequent modulations of corticospinal excitability during action observation. However, results were at odds with a strict version of the direct matching hypothesis that would suggest the opposite pattern. In fact, the more the actor\u2019s movement was similar to the observer\u2019s individual motor signature, the smaller was the MEPs amplitude, and vice versa. These results conform to the predictive coding hypothesis, suggesting that during AO, the motor system compares our own way of doing the action (individual motor signature) with the action displayed on the screen (actor\u2019s movement). 3) In the third study, we investigated the neural mechanisms underlying the visual perception of action mistakes. According to a strict version of the direct matching hypothesis, the observer should potentially reproduce the neural activation present during the actual execution of action errors (van Schie et al. 2004). Here, instead of observing an increase of cortical inhibition, we showed an early (120 ms) decrease of intracortical inhibition (short intracortical inhibition) when a mismatch was present between the observed action (erroneous) and the observer\u2019s expectation. As proposed by the predictive coding framework, the motor system may be involved in the generation of an error signal potentially relying on an early decrease of intracortical inhibition within the corticomotor system. The second line of research aimed at the investigation of how sensorimotor communication flows between agents engaged in a complementary action coordination task. In this regard, measures of interest where related to muscle activity and/or kinematics as the recording of TMS-related indexes would be too complicated in a joint-action scenario. 1) In the first study, we exploited the known phenomenon of Anticipatory Postural Adjustments (APAs). APAs refers to postural adjustments made in anticipation of a self- or externally-generated disturbance in order to cope for the predicted perturbation and stabilize the current posture. Here we examined how observing someone else lifting an object we hold can affect our own anticipatory postural adjustments of the arm. We showed that the visual information alone (joint action condition), in the absence of efference copy (present only when the subject is unloading by himself the object situated on his hand), were not sufficient to fully deploy the needed anticipatory muscular activations. Rather, action observation elicited a dampened APA response that is later augmented by the arrival of tactile congruent feedback. 2) In a second study, we recorded the kinematic of orchestra musicians (one conductor and two lines of violinists). A manipulation was added to perturb the normal flow of information conveyed by the visual channel. The first line of violinist where rotated 180\ub0, and thus faced the second line. Several techniques were used to extract inter-group (Granger Causality method) and intra-group synchronization (PCA for musicians and autoregression for conductors). The analyses were directed to two kinematic features, hand and head movements, which are central for functionally different action. The hand is essential for instrumental actions, whereas head movements encode ancillary expressive actions. During the perturbation, we observed a complete reshaping of the whole patterns of communication going in the direction of a distribution of the leadership between conductor and violinists, especially for what regards head movements. In fact, in the perturbed condition, the second line acts as an informational hub connecting the first line to the conductor they no longer can see. This study evidences different forms of communications (coordination versus synchronization) flowing via different channels (ancillary versus instrumental) with different time-scales

Mechanical engineering challenges in humanoid robotics

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 36-39).Humanoid robots are artificial constructs designed to emulate the human body in form and function. They are a unique class of robots whose anthropomorphic nature renders them particularly well-suited to interact with humans in a world designed for humans. The present work examines a subset of the plethora of engineering challenges that face modem developers of humanoid robots, with a focus on challenges that fall within the domain of mechanical engineering. The challenge of emulating human bipedal locomotion on a robotic platform is reviewed in the context of the evolutionary origins of human bipedalism and the biomechanics of walking and running. Precise joint angle control bipedal robots and passive-dynamic walkers, the two most prominent classes of modem bipedal robots, are found to have their own strengths and shortcomings. An integration of the strengths from both classes is likely to characterize the next generation of humanoid robots. The challenge of replicating human arm and hand dexterity with a robotic system is reviewed in the context of the evolutionary origins and kinematic structure of human forelimbs. Form-focused design and function-focused design, two distinct approaches to the design of modem robotic arms and hands, are found to have their own strengths and shortcomings. An integration of the strengths from both approaches is likely to characterize the next generation of humanoid robots.by Peter Guang Yi Lu.S.B

Enhanced Rescue Lift Capability

The evolving and ever-increasing demands of emergency response and disaster relief support provided by rotorcraft dictate, among other things, the development of enhanced rescue lift capability for these platforms. This preliminary analysis is first-order in nature but provides considerable insight into some of the challenges inherent in trying to effect rescue using a unique form of robotic rescue device deployed and operated from rotary-wing aerial platforms