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Photo and kinematic structure of the humanoid robot Lola. Joint distribution is shown on the right side
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Autonomous navigation in complex environments featuring obstacles, varying ground compositions, and external disturbances requires real-time motion generation and stabilization simultaneously. In this paper, we present and evaluate a strategy for rejection of external disturbances and real-time motion generation in the presence of obstacles and non...
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Citations
... This allowed rapid reaction to external disturbances by adaptive stepping leading to balance recovery and improved localization accuracy. Hildebrandt et al. [69] used the point cloud from an RGB-D camera to model obstacles as swept-sphere-volumes (SSVs) and step-able surfaces as convex polygons for real-time reactive footstep planning with the Lola humanoid robot. Their system was capable of handling rough terrain as well as external disturbances such as pushes (see Fig. 3). ...
Purpose of Review
The field of humanoid robotics, perception plays a fundamental role in enabling robots to interact seamlessly with humans and their surroundings, leading to improved safety, efficiency, and user experience. This scientific study investigates various perception modalities and techniques employed in humanoid robots, including visual, auditory, and tactile sensing by exploring recent state-of-the-art approaches for perceiving and understanding the internal state, the environment, objects, and human activities.
Recent Findings
Internal state estimation makes extensive use of Bayesian filtering methods and optimization techniques based on maximum a-posteriori formulation by utilizing proprioceptive sensing. In the area of external environment understanding, with an emphasis on robustness and adaptability to dynamic, unforeseen environmental changes, the new slew of research discussed in this study have focused largely on multi-sensor fusion and machine learning in contrast to the use of hand-crafted, rule-based systems. Human robot interaction methods have established the importance of contextual information representation and memory for understanding human intentions.
Summary
This review summarizes the recent developments and trends in the field of perception in humanoid robots. Three main areas of application are identified, namely, internal state estimation, external environment estimation, and human robot interaction. The applications of diverse sensor modalities in each of these areas are considered and recent significant works are discussed.
... Autonomous navigation in complex environments requires real-time motion generation and stability control in environments with obstacles, changing ground composition, and external disturbances. It will be widely used in practical applications only when leg robots can reliably walk and navigate complex scenes [5]. However, this will bring multiple challenges to bipedal robots in complex scenes: (1) the robot must solve the problem of autonomous motion generation in complex environments; (2) the robot must be able to respond quickly to dynamic changes in the environment or user input [6]; (3) the robot motion must be reliable and robust in the presence of unknown disturbances or modeling errors [7]; and (4) the robot must ensure the safety of the surrounding environment and itself. ...
Reinforcement learning provides a general framework for achieving autonomy and diversity in traditional robot motion control. Robots must walk dynamically to adapt to different ground environments in complex environments. To achieve walking ability similar to that of humans, robots must be able to perceive, understand and interact with the surrounding environment. In 3D environments, walking like humans on rugged terrain is a challenging task because it requires complex world model generation, motion planning and control algorithms and their integration. So, the learning of high-dimensional complex motions is still a hot topic in research. This paper proposes a deep reinforcement learning-based footstep tracking method, which tracks the robot’s footstep position by adding periodic and symmetrical information of bipedal walking to the reward function. The robot can achieve robot obstacle avoidance and omnidirectional walking, turning, standing and climbing stairs in complex environments. Experimental results show that reinforcement learning can be combined with real-time robot footstep planning, avoiding the learning of path-planning information in the model training process, so as to avoid the model learning unnecessary knowledge and thereby accelerate the training process.
... There is an important feature in navigation for steel bridge inspection robots: the dimensions of steel bars are limited, and the robots have small space to make a motion. The methods in Deits & Tedrake (2015); Jatsun et al. (2017); Hildebrandt et al. (2019) are able to build very nice convex regions, which make the construction of configuration space easy. The approximation methods, however, reduce the dimension of the workspace, and could make the robot motion infeasible. ...
... This is a popular problem in legged-robot, which has been investigated carefully in Deits & Tedrake (2017), the authors proposed the convex-based algorithms, which deployed convex optimization problem to determine an obstacle-free ellipsoid (convex one), then estimate step-able areas for a biped robot. In Hildebrandt et al. (2019), the authors proposed an algorithm to determine the valid convex collision-free regions with geometrical constraints of obstacles. In those algorithms, a portion of the step-able area, especially as the vertex number is small, was not considered due to the convex approximation. ...
Autonomous navigation of steel bridge inspection robots is essential for proper maintenance. The majority of existing robotic solutions for steel bridge inspection requires human intervention to assist in the control and navigation. In this paper, a control and navigation framework has been proposed for the steel bridge inspection robot developed by the Advanced Robotics and Automation (ARA)to facilitate autonomous real-time navigation and minimize human intervention. The ARA robot is designed to work in two modes: mobile and inch-worm. The robot uses mobile mode when moving on a plane surface and inch-worm mode when jumping from one surface to the other. To allow the ARA robot to switch between mobile and inch-worm modes, a switching controller is developed with 3D point cloud data based. The surface detection algorithm is proposed to allow the robot to check the availability of steel surfaces (plane, area, and height) to determine the transformation from mobile mode to inch-worm one. To have the robot safely navigate and visit all steel members of the bridge, four algorithms are developed to process the data from a depth camera, segment it into clusters, estimate the boundaries, construct a graph representing the structure, generate the shortest inspection path with any starting and ending points, and determine available robot configuration for path planning. Experiments on steel bridge structures setup highlight the effective performance of the algorithms, and the potential to apply to the ARA robot to run on real bridge structures.
... With the limit of steel bar dimension, There is an important feature in navigation for steel bridge inspection robots: the dimension of steel bars are limited, and the robots have small space to make a motion. The methods in [10]- [12] are able to build very nice convex regions, which make the construction of configuration space easy. The approximation methods, however, reduce the dimension of the workspace, and could make the robot motion infeasible. ...
Autonomous navigation is essential for steel bridge inspection robot to monitor and maintain the working condition of steel bridges. Majority of existing robotic solutions requires human support to navigate the robot doing the inspection. In this paper, a navigation framework is proposed for ARA robot [1], [2] to run on mobile mode. In this mode, the robot needs to cross and inspect all the available steel bars. The most significant contributions of this research are four algorithms, which can process the depth data, segment it into clusters, estimate the boundaries, construct a graph to represent the structure, generate a shortest inspection path with any starting and ending points, and determine available robot configuration for path planning. Experiments on steel bridge structures setup highlight the effective performance of the algorithms, and the potential to apply to the ARA robot to run on real bridge structures. We released our source code in Github for the research community to use.
... Previously developed robots often rely on surface-profile information, according to which they make walking-pattern changes by controlling their jointmotor angles for overcoming or avoiding obstacles. Typically, the environment information is collected by cameras or similar vision-based sensors [19]- [20]. Therefore, the case of a ''blind'' humanoid robot, without any camera to sense the environment, can be a worst-case scenario for robot-stability control [16]- [18]. ...
An experimental and theoretical study of real-time robot balancing on inclined surfaces with electrical feedback circuitry is presented. Force sensors are experimentally shown to extend the sustainability of a stable robot posture beyond a critical surface inclination. For this purpose, the inclination feedback from the force sensors is used to adjust the robot’s ankle-pitch-motor angle above the critical inclination, thus enabling the maintenance of a stable robot posture. Further, the Inverted Pendulum Model (IPM) (Hemami and Golliday, 1977, Hemami
et al.
, 1973, and McGhee and Kuhner, 1969) is extended to the case of inclined surfaces. Through application of this extended IPM it is demonstrated, that simultaneous use of gyro-sensor data can minimize the necessary initial adjustment of the motor angle for controlled robot-body rotation, which additionally has the positive effect of reducing possible overshoots of the motor’s rotation angle during feedback. Consequently, the reported feedback control improves the robot-body stability on inclined surfaces. Efficient implementation of the developed control scheme into an existing robot’s electrical system is proposed.
... These models govern the planning and control of most modern walking robots. The main aim is to either simplify or optimize the control strategy [14]- [16] or to robustly utilize the dynamics in a more convenient manner [17], [18] among other criterion [19]. ...
Spring Loaded Pantographs (SLPs) are frequently used in designing lightweight limbs for multi-legged robots. Quadruped robots that incorporate cable-pulled SLP legs have proven to be agile, robust and capable of conserving energy during their gait cycle. In such designs, the extension of the distal segments via the knee joint is dependent upon the length of the cable. In this article we propose the use of an Elastically Loaded Scissors Mechanism (ELS Mechanism or ELSM), which is a variant of the SLP. Driven by ’pulling’ onto the proximal joint of the scissors as opposed to the distal joint, this proposed leg utilizes the increased mechanical advantage of the scissors mechanism to ’amplify’ input angles to larger output displacement by the knee joint. Analysis and Simulations reveal that the proposed mechanism achieves increased motion speed as compared to the SLP mechanism. This, however, comes at the cost of higher load on the actuator which serves as an engineering trade-off. This is validated by experimentation using motion capture and load motor techniques of the SLP and ELS configurations in a physical quadruped robot.
... Legged locomotion on humanoid robots like ASIMO and BIPER having superior means of walking and maintaining a balanced posture when combined with suitable walking pattern generation has shown to be suitable for preventing collisions [6]. As the aspect of collision avoidance based on the perceived information about the surrounding environment highly allows a safer walking, it's beneficial to target collision avoidance and step generating in cluttered environments [7][8]. To do so most humanoids employ vision system to examine the environment and prevent collisions. ...
... It is a well-known fact that human beings can rely on their hands to protect themselves in case of falling and have a more balanced posture when compared to humanoids. Due to humanoids' close physical characteristics to humans they can also benefit from using their hands and other body parts besides their feet for balance enhancement [7][8][9][10][11]. With improved and comprehensive methodologies to maintain balanced, humanoids will reach safer close-proximity interactions with humans. ...
... With improved and comprehensive methodologies to maintain balanced, humanoids will reach safer close-proximity interactions with humans. However, to fulfil this vision humanoids need to engage complementary technologies and methods to their current sensor and motion systems to assure effective handling of systematic errors/disturbances [7]. ...
... Unfortunately, RANSAC is prone to report points that belong to unrelated, but coplanar surfaces. Wahrmann et al. [5], [16] also use RANSAC to identify planes, but split them into clusters later with the help of a 2D grid. The clusters are then converted to convex polygons with a fixed number of corners to represent walking surfaces. ...
... It is essential to ensure the availability of sufficient area for successful robot transition. This is a popular problem in legged-robot, which is investigated carefully in [16]- [18]. In [16], [17], the authors proposed the convex-based algorithms, which deployed convex optimization problem to determine an obstacle-free ellipsoid (convex one), then estimate stepable areas for biped robot. ...
... In [16], [17], the authors proposed the convex-based algorithms, which deployed convex optimization problem to determine an obstacle-free ellipsoid (convex one), then estimate stepable areas for biped robot. In [18], the authors proposed an algorithm to determine the valid convex collision-free regions with geometrical constraints of obstacles. In those algorithms, a portion of the step-able area, especially as the vertex number is small, was not considered due to the convex approximation. ...
Autonomous navigation of steel bridge inspection robots is essential for proper maintenance. The majority of existing robotic solutions for bridge inspection require human intervention to assist in the control and navigation. In this paper, a control system framework has been proposed for a previously designed ARA robot [1], which facilitates autonomous real-time navigation and minimizes human involvement. The mechanical design and control framework of ARA robot enables two different configurations, namely the mobile and inch-worm transformation. In addition, a switching control was developed with 3D point clouds of steel surfaces as the input which allows the robot to switch between mobile and inch-worm transformation. The surface availability algorithm (considers plane, area, and height) of the switching control enables the robot to perform inch-worm jumps autonomously. Themobiletransformationallows the robot to move on continuous steel surfaces and perform visual inspection of steel bridge structures. Practical experiments on actual steel bridge structures highlight the effective performance of ARA robot with the proposed control framework for autonomous navigation during a visual inspection of steel bridges.
... It is essential to ensure the availability of sufficient area for successful robot transition. This is a popular problem in legged-robot, which is investigated carefully in [16]- [18]. In [16], [17], the authors proposed the convex-based algorithms, which deployed convex optimization problem to determine an obstacle-free ellipsoid (convex one), then estimate stepable areas for biped robot. ...
... In [16], [17], the authors proposed the convex-based algorithms, which deployed convex optimization problem to determine an obstacle-free ellipsoid (convex one), then estimate stepable areas for biped robot. In [18], the authors proposed an algorithm to determine the valid convex collision-free regions with geometrical constraints of obstacles. In those algorithms, a portion of the step-able area, especially as the vertex number is small, was not considered due to the convex approximation. ...
Autonomous navigation of steel bridge inspection robots are essential for proper maintenance. Majority of existing robotic solutions for bridge inspection require human intervention to assist in the control and navigation. In this paper, a control system framework has been proposed for a previously designed ARA robot [1], which facilitates autonomous real-time navigation and minimizes human involvement. The mechanical design and control framework of ARA robot enables two different configurations, namely the mobile and inch-worm transformation. In addition, a switching control was developed with 3D point clouds of steel surfaces as the input which allow the robot to switch between mobile and inch-worm transformation. The surface availability algorithm (considers plane, area and height) of the switching control enables the robot to perform inch-worm jumps autonomously. The mobile transformation allows the robot to move on continuous steel surfaces and perform visual inspection of steel bridge structures. Practical experiments on actual steel bridge structures highlight the effective performance of ARA robot with the proposed control framework for autonomous navigation during visual inspection of steel bridges.
