Teleoperation of Humanoid Robots: A Survey Darvish, Kourosh; Penco, Luigi; Ramos, Joao ...
IEEE transactions on robotics,
06/2023, Letnik:
39, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Teleoperation of humanoid robots enables the integration of the cognitive skills and domain expertise of humans with the physical capabilities of humanoid robots. The operational versatility of ...humanoid robots makes them the ideal platform for a wide range of applications when teleoperating in a remote environment. However, the complexity of humanoid robots imposes challenges for teleoperation, particularly in unstructured dynamic environments with limited communication. Many advancements have been achieved in the last decades in this area, but a comprehensive overview is still missing. This survey article gives an extensive overview of humanoid robot teleoperation, presenting the general architecture of a teleoperation system and analyzing the different components. We also discuss different aspects of the topic, including technological and methodological advances, as well as potential applications.
As robotics technology evolves, we believe that personal social robots will be one of the next big expansions in the robotics sector. Based on the accelerated advances in this multidisciplinary ...domain and the growing number of use cases, we can posit that robots will play key roles in everyday life and will soon coexist with us, leading all people to a smarter, safer, healthier, and happier existence.
We describe the research and the integration methods we developed to make the HRP-2 humanoid robot climb vertical industrial-norm ladders. We use our multi-contact planner and multi-objective ...closed-loop control formulated as a QP (quadratic program). First, a set of contacts to climb the ladder is planned off-line (automatically or by the user). These contacts are provided as an input for a finite state machine. The latter builds supplementary tasks that account for geometric uncertainties and specific grasps procedures to be added to the QP controller. The latter provides instant desired states in terms of joint accelerations and contact forces to be tracked by the embedded low-level motor controllers. Our trials revealed that hardware changes are necessary, and parts of software must be made more robust. Yet, we confirmed that HRP-2 has the kinematic and power capabilities to climb real industrial ladders, such as those found in nuclear power plants and large scale manufacturing factories (e.g. aircraft, shipyard) and construction sites.
An artificial nociceptor realized with a single 2D MoS2-based memristor device is demonstrated in this work. The threshold switching memristor (TSM) device exhibits volatile resistance switching ...characteristics with low threshold voltage and a high ON-OFF ratio of 106. The Au/MoS2/Ag TSM device imitates a nociceptor, a special receptor of a sensory neuron that can detect noxious stimulus and transfer the signal to the central nervous system for preventive actions. The single device exhibits all key features of nociceptors including threshold, relaxation, "no adaptation" and sensitization phenomena of allodynia and hyperalgesia depending on the strength, duration, and repetition of the external stimuli. This work indicates applicability of this device in artificial sensory alarm systems for humanoid robots.
Learning dexterous in-hand manipulation Andrychowicz, OpenAI: Marcin; Baker, Bowen; Chociej, Maciek ...
The International journal of robotics research,
01/2020, Letnik:
39, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We use reinforcement learning (RL) to learn dexterous in-hand manipulation policies that can perform vision-based object reorientation on a physical Shadow Dexterous Hand. The training is performed ...in a simulated environment in which we randomize many of the physical properties of the system such as friction coefficients and an object’s appearance. Our policies transfer to the physical robot despite being trained entirely in simulation. Our method does not rely on any human demonstrations, but many behaviors found in human manipulation emerge naturally, including finger gaiting, multi-finger coordination, and the controlled use of gravity. Our results were obtained using the same distributed RL system that was used to train OpenAI Five. We also include a video of our results: https://youtu.be/jwSbzNHGflM.
In this paper, we propose a biped walking controller that optimized three push recovery strategies: the ankle, hip, and stepping strategies. We suggested formulations that related the effects of each ...strategy to the stability of walking based on the linear inverted pendulum with flywheel model. With these relations, we could set up an optimization problem that integrates all the strategies, including step time change. These strategies are not applied hierarchically, but applied according to each weighting factor. Various combinations of weighting factors can be used to determine how the robot should respond to an external push. The optimization problem derived here includes many nonlinear components, but it has been linearized though some assumptions and it can be applied to a robot in real time. Our method is designed to be robust to modeling errors or weak perturbations, by exploiting the advantages of the foot. Hence, it is very practical to apply this algorithm to a real robot. The effectiveness of the walking controller has been verified through abstracted model simulation, full dynamics simulation, and a practical robot experiments.
Stability control for humanoid robots based on zero moment point (ZMP) control and impedance control are widespread. However, uncertain changes in the center of mass (CoM) height for ZMP control and ...specific regulation of the variable stiffness of impedance control have been challenging issues in previous studies. In this article, these two problems are solved by implementing fuzzy control-based regulations. First, the fuzzy ZMP controller, which regulates the feedback gains online based on the CoM height change and CoM tracking errors, is proposed. Second, we propose a fuzzy regulation law for variable stiffness, which is applied for uncertain contact situations and inspired by the pattern of human muscle stiffness. With these two methods, the ground adaptability for humanoid robots is enhanced. The proposed method is validated with experiments on a real robot platform, BHR-T.
We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a ...neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.
Redundant mechanical systems like humanoid robots are designed to fulfill multiple tasks at a time. A task, in velocity-resolved inverse kinematics, is a desired value for a function of the robot ...configuration that can be regulated with an ordinary differential equation (ODE). When facing simultaneous tasks, the corresponding equations can be grouped in a single system or, better, sorted in priority and solved each in the solutions set of higher priority tasks. This elegant framework for hierarchical task regulation has been implemented as a sequence of least-squares problems. Its limitation lies in the handling of inequality constraints, which are usually transformed into more restrictive equality constraints through potential fields. In this paper, we propose a new prioritized task-regulation framework based on a sequence of quadratic programs (QP) that removes the limitation. At the basis of the proposed algorithm, there is a study of the optimal sets resulting from the sequence of QPs. The algorithm is implemented and illustrated in simulation on the humanoid robot HRP-2.
Wheeled-legged humanoid robots combine the rough terrain compliance of humanoid robots with the high efficiency of wheeled robots, enabling the robot to achieve flexible and stable locomotion over ...multiple terrains. However, the stability control of the wheel-legged humanoid robot in dealing with rough terrains and unexpected external disturbances remains unsolved. In the current investigation, a compliant balance control framework (CBCF) is proposed, which can absorb ground shocks, withstand unexpected external disturbances, and remain stable posture during motion. The CBCF connects the control of legs movement and the wheels balance control through the movement of the robot's center of mass. The wheel balance control employs the inverted pendulum model and controls the two wheels through model prediction. The leg posture control utilizes a whole-body dynamic compensator to realize the compliant motion and remain a stable posture. Cooperating with the high-level motion planner, the CBCF can allow the BHR-WI to move quickly and perform excellent adaptation in unmodeled rough terrains, and it is able to appropriately handle unexpected external disturbances as well. It is also worth mentioning that the BHR-WI is capable of remaining balance and quickly recovering stability in the event of a disturbance, even if one of the legs leaves the ground. Finally, tests confirm that the BHR-WI could withstand sustained unexpected disturbances, could smoothly cross the grass and steps and even realize high maneuverability in jumping.
PDF
