Conventional Robots Research Articles

Reconfigurable Soft Robots by Building Blocks.

Soft robots are of increasing interest as they can cope with challenges that are poorly addressed by conventional rigid-body robots (e.g., limited flexibility). However, due to their flexible nature, the soft robots can be particularly prone to exploit modular designs for enhancing their reconfigurability, that is, a concept which, to date, has not been explored. Therefore, this paper presents a design of soft building blocks that can be disassembled and reconfigured to build different modular configurations of soft robots such as robotic fingers and continuum robots. First, a numerical model is developed for the constitutive building block allowing to understand their behavior versus design parameters, then a shape optimization algorithm is developed to permit the construction of different types of soft robots based on these soft building blocks. To validate the approach, 2D and 3D case studies of bio-inspired designs are demonstrated: first, soft fingers are introduced as a case study for grasping complex and delicate objects. Second, an elephant trunk is used for grasping a flower. Third, a walking legged robot. These case studies prove that the proposed modular building approach makes it easier to build and reconfigure different types of soft robots with multiple complexshapes.

Bioinspired hydrogel jellyfish with mechanical flexibility and acoustic transparency

The uniqueness of soft materials such as hydrogels allows for great potential for new soft robots and actuators. Conventional underwater robots are generally crafted of rigid structures and materials with water-mismatched acoustic impedance, severely limiting their underwater operating capabilities. Therefore, flexible and acoustically transparent soft robots show great prospects for applications in marine exploration, biomedical engineering, etc. Inspired by the high water content of jellyfish, we report a hydraulically actuated bioinspired hydrogel jellyfish. The acoustic backscattered energy of the hydrogel jellyfish is reduced to about 1/270 compared with conventional underwater robots, achieving omnidirectional transparency under broadband acoustic detection from 10 kHz to 1 MHz. Moreover, the body length of hydrogel jellyfish can contract to about 1/3 of its original length under hydraulic control, exhibiting flexible motion to pass through narrow orifices. This design can potentially establish generic design principles for constructing next-generation mechanically flexible and acoustically transparent robots. • Jellyfish robot combines high water content of jellyfish and programmable hydrogel • Hydrogel jellyfish robot exhibits excellent acoustic transparency • High mechanical flexibility enables passing through narrow orifices Conventional underwater robots are generally crafted of rigid structures and materials with water-mismatched acoustic impedance. Inspired by jellyfish, Zhang et al. report a hydrogel jellyfish robot that achieves flexibility and near-water acoustic impedance. This work may establish design principles for constructing mechanically flexible and acoustic transparent robots.

Magnetic-Directed Manipulation and Assembly of Fragile Bioartificial Architectures in the Liquid–Liquid Interface

Assembling has been regarded as one of the most potential methods for fabricating complex structures with better performance and richer features, especially at nano/micro scale. Despite the recent achievement in micromanipulation and assembly, including self-assembling, mechanical micromanipulator, and noncontact operation, the manipulation and assembly of flexible and fragile microstructures in an enclosed environment for biomedical applications are still challenging. In this work, we proposed a method to assemble untethered and fragile hydrogel structures (building units) in the liquid–liquid interface by a magnetic microcapsule-robot (MMc-robot). Different from the conventional magnetic robot, a semipermeable alginate–chitosan–alginate layer is adopted to encapsulate magnetic particles to make the MMc-robot biocompatible, during which, the designed lock-and-key shape not only allows the grabbing between MMc-robot and building units but also ensures the reliable forward force as well as steering torque transmission. To constrain the building units in the same plane while keeping the structural integrity and movement flexibility, we conduct the experiment in the liquid–liquid interface. Moreover, the corresponding mechanical analysis, dynamic modeling, and control strategy are provided for the manipulation and assembly of units. The successful results in magnetic-directed assembly of untethered and fragile microstructures in the liquid–liquid interface verify the feasibility as well as practicality of theproposed manipulation and assembling methods. This research provides a new prospect for the manipulation and assembly of flexible bioartificial architectures, which shows promise in 3-D complex structures fabrication from biomimetics to tissue engineering.

Adopting Physical Artificial Intelligence in Soft Aerial Robots

In recent years, there has been a lot more attention towards the utilization of physically intelligent features in robotics. In this work, we provide a perspective on the physical artificial intelligence (PAI) paradigm and its impact on the conceptualization, design, and manufacturing of current and future aerial robots and infrastructure. We highlight the theory, enabling technologies, system features, and the tasks that the PAI paradigm will improve beyond the current approaches with conventional rigid aerial robots. We also discuss the multi-disciplinary effort required to collaborate with and educate researchers in the development of physically intelligent robots. PAI promises to lead the development of a new era of robust flying robotic organisms that are capable of adapting to and performing multi-functional tasks autonomously in a complex and unstructured environment. Aerial robotics is a great field of study to validate PAI as a development methodology.

Modelling and Analysis of the Spital Branched Flexure-Hinge Adjustable-Stiffness Continuum Robot

Continuum robots are increasingly being used in industrial and medical applications due to their high number of degrees of freedom (DoF), large workspace and their ability to operate dexterously. However, the positional accuracy of conventional continuum robots with a backbone structure is usually low due to the low stiffness of the often-lengthy driving cables/tendons. Here, this problem has been solved by integrating additional mechanisms with adjustable stiffness within the continuum robot to improve its stiffness and mechanical performance, thus enabling it to be operated with high accuracy and large payloads. To support the prediction of the improved performance of the adjustable stiffness continuum robot, a kinetostatic model was developed by considering the generalized internal loads that are caused by the deformation of the flexure-hinge mechanism and the structural stiffening caused by the external loads on the end-effector. Finally, experiments were conducted on physical prototypes of 2-DoF and 6-DoF continuum robots to validate the model. It was found that the proposed kinetostatic model validates experimental observations within an average deviation of 9.1% and 6.2% for the 2-DoF and 6-DoF continuum robots, respectively. It was also found that the kinematic accuracy of the continuum robots can be improved by a factor of 32.8 by adding the adjustable stiffness mechanisms.

Structural design and analysis of pneumatic prostate seed implantation robot applied in magnetic resonance imaging environment.

The method of MRI (Magnetic Resonance Imaging) image-guided robot for prostate seed implantation has developed rapidly in recent years. During the operation, although the puncture effect guided by MRI is very good, it is difficult for conventional robots driven by motors to work normally in this environment, which reduces the accuracy of seed implantation and affects the treatment effect. First, this paper designs a pneumatic prostate seed implantation robot that is compatible with MRI; the robot is composed of an execution module and an adjustment module, and can complete the positioning and adjustment of the robot's needle entry point, the pose adjustment of the puncture needle and the completion of seed implantation in the MRI space; meanwhile, the statics simulation analysis of its key components is carried out. Then, the kinematics analysis was carried out according to the designed robot structure, and the relationship between the posture of the needle tip and the change of the pneumatic cylinder was obtained; meanwhile, using MATLAB 2020 software, combined with the method of Monte Carlo random number sampling, the simulation analysis of the workspace was carried out. Finally, an experimental prototype is constructed to conduct puncture accuracy experiments, workspace experiments and performance comparison tests in MRI environment. The statics simulation results verify that the key components of the robot designed in this paper can meet the strength requirements of the robot. The simulation results of the workspace meet the requirements of space surgery for prostate seed implantation under the guidance of MRI environment. The puncture accuracy experimented to verify that increasing the puncture speed can improve the seed implantation accuracy, and the puncture deviation of the robot is less than the average deviation of the doctor's actual operation by 6.5mm. The working space experiment shows that the pitch range is -23.3°~27.8°, the movement range in the X direction is 0~210mm, the movement range in the Y direction is 0~101mm, and the lifting range in the Z direction is 0~81mm, which meets the workspace requirements under MRI. The performance comparison test results in the MRI environment show that the robot is well compatible with MRI instruments. The pneumatic prostate seed implantation robot designed in this paper has a reasonable structure and stable dynamic performance output, and can perform precise surgical operations in the MRI strong magnetic environment. The research work in this paper provides a design reference for the related research on the positioning accuracy of minimally invasive puncture surgery guided by MRI images.

Real-Time Reconfiguration Planning for the Dynamic Control of Reconfigurable Cable-Driven Parallel Robots

Abstract The movable anchor points make reconfigurable cable-driven parallel robots (RCDPRs) advantageous over conventional cable-driven parallel robots with fixed anchor points, but the movable anchor points also introduce an inherent problem—reconfiguration planning. Scholars have proposed reconfiguration planning approaches for RCDPRs, taking into account the statics and kinematics of RCDPRs. However, a real-time reconfiguration planning approach that considers the dynamics of an RCDPR and is computationally efficient enough to be integrated into the RCDPR's dynamic controller is still not available in the literature yet. This paper develops a real-time reconfiguration planning approach for RCDPRs. A novel reconfiguration value function is defined to reflect the “value” of an RCDPR configuration and provide a reference index for the reconfiguration planning of an RCDPR. And then, the developed approach conducts reconfiguration planning based on the value of RCDPR configurations. The developed approach is computationally efficient, reducing the reconfiguration planning time by more than 93%, compared to single iteration of a box-constrained optimization-based reconfiguration planning approach. Such a high efficiency allows the developed approach to be integrated into an RCDPR's dynamic controller that usually runs with a high frequency. Integrating reconfiguration planning and dynamic control enhances the control performance of the RCDPR. To verify the effectiveness of the developed approach and the integration of reconfiguration planning and dynamic control for RCDPRs, a case study of an RCDPR with seven cables and four movable anchor points is conducted.

모바일 매니퓰레이터의 엘리베이터 조작을 위한 HRI 시스템 구현

Unlike conventional industrial robots that operate in a limited manufacturing environment, service robots should be able to operate in various environments. Where there are many complex high-rise buildings, service robots require the ability to ride and control elevators. Furthermore, a human-robot interaction (HRI) approach is critical because service robots have the characteristics of interacting directly with humans. Therefore, this paper proposes an HRI system that enables direct elevator button manipulation to enable mobile manipulator robots to perform tasks in various high-rise building environments. The system is divided into three subsystems: elevator button recognition, command reception through voice recognition, and elevator button operation. Elevator button recognition and command reception through voice recognition receive the required topics and communicate with the lower end of the elevator button operation. Although the three distinct substructures interact with each other and are independent, they can be replaced by different algorithms at any time. Because of the same characteristics, the system can be applied to various mobile manipulators with different specifications. The experiment proceeds with pressing the button on floors B1-4 through voice recognition in a simulation environment and pressing the button on floors 5-7 without voice recognition. The experimental results compared the central positions of the button and end effector’s x, y, and z coordinates after control. The system, verified through simulation, has since been applied to real robots.

Energy-Efficient Path Planning of Reconfigurable Robots in Complex Environments

Planning the energy-efficient and collision-free paths for reconfigurable robots in complex environments is more challenging than conventional fixed-shaped robots due to their flexible degrees of freedom while navigating through tight spaces. This article presents a novel algorithm, energy-efficient batch informed trees* (BIT*) for reconfigurable robots, which incorporates BIT*, an informed, anytime sampling-based planner, with the energy-based objectives that consider the energy cost for robot’s each reconfigurable action. Moreover, it proposes to improve the direct sampling technique of informed RRT* by defining an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L^2$</tex-math></inline-formula> <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">greedy informed set</i> that shrinks as a function of the state with the maximum admissible estimated cost instead of shrinking as a function of the current solution, thereby improving the convergence rate of the algorithm. Experiments were conducted on a tetromino hinged-based reconfigurable robot as a case study to validate our proposed path planning technique. The outcome of our trials shows that the proposed approach produces energy-efficient solution paths, and outperforms existing techniques on simulated and real-world experiments.

AR-assisted digital twin-enabled robot collaborative manufacturing system with human-in-the-loop

The teleoperation and coordination of multiple industrial robots play an important role in today’s industrial internet-based collaborative manufacturing systems. The user-friendly teleoperation approach allows operators from different manufacturing domains to reduce redundant learning costs and intuitively control the robot in advance. Nevertheless, only a few preliminary works have been introduced very recently, let alone its effective implementation in the manufacturing scenarios. To address the gap, this research proposes a novel multi-robot collaborative manufacturing system with human-in-the-loop control by leveraging the cutting-edge augmented reality (AR) and digital twin (DT) techniques. In the proposed system, the DTs of industrial robots are firstly mapped to physical robots and visualize them in the AR glasses. Meanwhile, a multi-robot communication mechanism is designed and implemented, to synchronize the state of robots in the twin. Moreover, a reinforcement learning algorithm is integrated into the robot motion planning to replace the conventional kinematics-based robot movement with corresponding target positions. Finally, three interactive AR-assisted DT modes, including real-time motion control, planned motion control, and robot monitoring mode are generated, which can be readily switched by human operators. Two experimental studies are conducted on (1) a single robot with a commonly used peg-in-hole experiment, and (2) the motion planning of multi-robot collaborative tasks, respectively. From the experimental results, it can be found that the proposed system can well handle the multi-robot teleoperation tasks with high efficiency and owns great potentials to be adopted in other complicated manufacturing scenarios in the near future.

A Novel Sensor for Tissue Mechanical Property Detection During Robotic Surgery.

Haptic feedback relays important tissue mechanical properties to surgeons during open surgery. However, this information is lost during Robot-assisted Minimally Invasive Surgery (RMIS). Here we present a proof-of-concept for a novel instrument-integrated sensor that uses fiber Bragg grating (FBG) arrays to identify tissues based on mechanical properties. Subjects were tasked with sorting tissue phantoms based on hardness. When using a conventional surgical robot, the average error for novices (N=5) and the expert user was 22.5% and 12.5% respectively. This reduced to 2.5% and 0% when sorting with direct palpation by hand. In contrast, the senorized instrument with automated analysis was able to perform the task without any error across all trials. Clinical Relevance - The proposed sensor has the potential of identifying different tissues based on mechanical properties and thus characterize tumors and other relevant structures. It is envisaged that this will improve decision making process during RMIS and also provide useful sensory information for autonomous surgery.

Developing Intelligent Robots that Grasp Affordance.

Humans and robots operating in unstructured environments both need to classify objects through haptic exploration and use them in various tasks, but currently they differ greatly in their strategies for acquiring such capabilities. This review explores nascent technologies that promise more convergence. A novel form of artificial intelligence classifies objects according to sensory percepts during active exploration and decides on efficient sequences of exploratory actions to identify objects. Representing objects according to the collective experience of manipulating them provides a substrate for discovering causality and affordances. Such concepts that generalize beyond explicit training experiences are an important aspect of human intelligence that has eluded robots. For robots to acquire such knowledge, they will need an extended period of active exploration and manipulation similar to that employed by infants. The efficacy, efficiency and safety of such behaviors depends on achieving smooth transitions between movements that change quickly from exploratory to executive to reflexive. Animals achieve such smoothness by using a hierarchical control scheme that is fundamentally different from those of conventional robotics. The lowest level of that hierarchy, the spinal cord, starts to self-organize during spontaneous movements in the fetus. This allows its connectivity to reflect the mechanics of the musculoskeletal plant, a bio-inspired process that could be used to adapt spinal-like middleware for robots. Implementation of these extended and essential stages of fetal and infant development is impractical, however, for mechatronic hardware that does not heal and replace itself like biological tissues. Instead such development can now be accomplished in silico and then cloned into physical robots, a strategy that could transcend human performance.

Assessing System-Wide Safety Readiness for Successful Human–Robot Collaboration Adoption

Despite their undisputed potential, the uptake of collaborative robots remains below expectations. Collaborative robots (cobots) are used differently from conventional industrial robots. The current safety focus of collaborative workspaces is predominantly on the technological design; additional factors also need to be considered to cope with the emerging risks associated with complex systems. Cobot technologies are characterized by an inherent tradeoff between safety and efficiency. They introduce new, emergent risks to organizations and can create psychosocial impacts on workers. This leads to a confusing body of information and an apparent contradiction about cobot safety. Combined with a lack of safety knowledge, this impedes the introduction of cobots. A multi-step methodology was used, including a literature review and conceptual modeling. This article argues for the need for a system-wide safety awareness readiness assessment in the consideration phase of cobot implementation to alleviate the knowledge deficit and confusion. This work will benefit both researchers and practitioners. In addition, it defends the appropriateness of a maturity grid model for a readiness assessment tool. The building blocks for an easy-to-use and practically applicable tool are proposed, as well as an agenda for the next steps.

Development of a Wearable Upper Limb Rehabilitation Robot Based on Reinforced Soft Pneumatic Actuators

Dyskinesia of the upper limbs caused by stroke, sports injury, or traffic accidents limits the ability to perform the activities of daily living. Besides the necessary medical treatment, correct and scientific rehabilitation training for the injured joint is an important auxiliary means during the treatment of the effected upper limb. Conventional upper-limb rehabilitation robots have some disadvantages, such as a complex structure, poor compliance, high cost, and poor portability. In this study, a novel soft wearable upper limb rehabilitation robot (SWULRR) with reinforced soft pneumatic actuators (RSPAs) that can withstand high pressure and featuring excellent loading characteristics was developed. Driven by RSPAs, this portable SWULRR can perform rehabilitation training of the wrist and elbow joints. In this study, the kinematics of an SWULRR were analyzed, and the force and motion characteristics of RSPA were studied experimentally. The results provide a reference for the development and application of wearable upper limb rehabilitation robots. An experimental study on the rotation angle of the wrist and the pressure of the RSPA was conducted to test the effect of the rehabilitation training and verify the rationality of the theoretical model. The process of wrist rehabilitation training was tested and evaluated, indicating that SWULRR with RSPAs will enhance the flexibility, comfort, and safety of rehabilitation training. This work is expected to promote the development of wearable upper-limb rehabilitation robots based on modular reinforced soft pneumatic actuators.

Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR.

Conventional mobile robots employ LIDAR for indoor global positioning and navigation, thus having strict requirements for the ground environment. Under the complicated ground conditions in the greenhouse, the accumulative error of odometer (ODOM) that arises from wheel slip is easy to occur during the long-time operation of the robot, which decreases the accuracy of robot positioning and mapping. To solve the above problem, an integrated positioning system based on UWB (ultra-wideband)/IMU (inertial measurement unit)/ODOM/LIDAR is proposed. First, UWB/IMU/ODOM is integrated by the Extended Kalman Filter (EKF) algorithm to obtain the estimated positioning information. Second, LIDAR is integrated with the established two-dimensional (2D) map by the Adaptive Monte Carlo Localization (AMCL) algorithm to achieve the global positioning of the robot. As indicated by the experiments, the integrated positioning system based on UWB/IMU/ODOM/LIDAR effectively reduced the positioning accumulative error of the robot in the greenhouse environment. At the three moving speeds, including 0.3 m/s, 0.5 m/s, and 0.7 m/s, the maximum lateral error is lower than 0.1 m, and the maximum lateral root mean square error (RMSE) reaches 0.04 m. For global positioning, the RMSEs of the x-axis direction, the y-axis direction, and the overall positioning are estimated as 0.092, 0.069, and 0.079 m, respectively, and the average positioning time of the system is obtained as 72.1 ms. This was sufficient for robot operation in greenhouse situations that need precise positioning and navigation.

Comparative anatomy of quadruped robots and animals: a review

Animals can instantly exhibit versatile behaviors in response to their circumstances to survive in harsh natural environments. For example, many animals chase prey, escape from predators, forage, utilize tools, build nests, and breed, in accordance with their niches with limited resources. To gain a deeper understanding of the source of this versatility in animals and apply the principles of their body plans to robotics, the authors, who work in the robotics and anatomy fields, jointly review and compare the essential body structure differences between quadruped robots and animals. This review provides a comprehensive discussion of the various functions of animal bodies by particularly focusing on the anatomical structure and gives examples of how these functions have been implemented in robotics. Conventional biomimetic robots have taken the approach of realizing animal functions as simple single-functional modules in order to achieve specific animal functions in the most efficient way. In contrast, animals have situation-dependent multi-functionality, in which one part of the body exhibits multiple capabilities depending on the situation. This new ‘polysemantic body’ design principle would transform the traditional processes for understanding and mimicking animals and make the interaction between biology and robotics more fruitful.

Bioinspired Amphibious Origami Robot with Body Sensing for Multimodal Locomotion.

Animals have long captured the inspirations of researchers in robotics with their unrivaled capabilities of multimodal locomotion on land and in water, achieved by functionally versatile limbs. Conventional soft robots show infinite degrees-of-freedom (DOFs), making it hard to be actuated and conduct multiple movements especially for multimodal locomotion in different environments. An origami robot, which is capable of reversibly transforming the robotic shape by simple creases folding/unfolding, reveals advantages for imitating flexible movements of animals, thus drawing more and more attention. However, it poses substantial technological challenges for bioinspired design, sensing, and actuation of origami robots that can generate multimodal locomotion through performing complex morphologic deformation in different scenarios such as land and water. To relieve this issue, we propose a novel bioinspired amphibious origami machine with body sensing for multimodal locomotion. In this work, inspired by the peristalsis of inchworm and human swimming behaviors, a unique origami body with legs and origami arms is developed to enable the integrated robot to move both on land and in water. Instead of traditional electronic sensors, we design highly stretchable and foldable layer resistive sensor with conductive polymers coated onto the origami body to achieve robotic sensing such as obstacle detection. In addition, with detailed analysis, a self-designed pneumatic system of time division, multiplexing, and serialization is adopted to efficiently control the robot with high DOF. We eventually demonstrate that the fabricated origami robot successfully moves in amphibious environments, which is capable of crawling forward, turning right/left, and swimming. We expect that this work indicates contributions to advanced origami design, actuation control, and body sensor of the bioinspired robot with multimodal locomotion for broadly practical applications.

Wheel Arrangement of Four Omni Wheel Mobile Robot for Compactness

Compact omnidirectional mobile robots are required to automate transportation of raw materials, products, etc. within an industrial plant. This paper focuses on omni wheel robots with low vibration and wheel arrangements that contribute to compactness. Due to its wheels’ configuration, our proposed compact robot may have different sensitivity to noise (controller) and different performance (errors) when following a predetermined path, compared to conventional ones. Using a simple DC motor, a robot with the proposed arrangement and a conventional robot run along a predetermined path. A linear–quadratic regulator that is processed lightly is used to control the robots for practicality. As a result, the robot’s trajectory in the proposed arrangement showed a distortion different from that of the conventional type. The distortion of the trajectory was attributed to the inability of the DC motor to rotate stably at low speed. The different distortions exhibited suggest that the wheel arrangement changes the effect of imperfect control on the robot’s motion. In addition, the proposed arrangement showed the possibility of being suitable for a transport robot because the wheels are placed in the four corners of the robot, facing forward, backward, left, and right.

Task-Oriented Evaluation of the Feasible Kinematic Directional Capabilities for Robot Machining.

Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior to task execution, for which we need efficient algorithms, especially in the case of flexible robot applications. To provide accurate and physically consistent information about the maximum kinematic capabilities while considering the requirements of the task, an approach called the Decomposed Twist Feasibility (DTF) method is proposed in this study. The evaluation of the maximum feasible end-effector velocity is based on the idea of decomposition into the linear and angular motion capabilities, considering a typical robot machining task with synchronous linear and angular motion. The proposed DTF method is presented by the well-known manipulability polytope concept. Unlike the existing methods that estimate the kinematic performance capabilities in arbitrarily weighted twist space, or separately in the translation and the rotation subspace, our approach offers an accurate and simple solution for the determination of the total kinematic performance capabilities, which is often highly required, especially in the case of robot machining tasks. The numerical results obtained in this study show the effectiveness of the proposed approach. Moreover, the proposed DTF method could represent suitable kinematic performance criteria for the optimal placement of predefined tasks within the robot workspace.

Design of Transverse Brachiation Robot and Motion Control System for Locomotion between Ledges at Different Elevations.

Bio-inspired transverse brachiation robots mimic the movement of human climbers as they traverse along ledges on a vertical wall. The constraints on the locomotion of these robots differ considerably from those of conventional brachiation robots due primarily to the need for robust hand-eye coordination. This paper describes the development of a motion control strategy for a brachiation robot navigating between wall ledges positioned on a level plane or at different elevations. We based our robot on a four-link arm-body-tail system performing a four-phase movement, including a release phase, body reversal phase, swing-up phase, and grasping phase. We designed a gripper that uses passive wrist joint motion to grasp the ledge during the tail swing. We also developed a dynamic model by which to coordinate the swing-up movement, define the phase switching conditions, and time the grasping action of the grippers. In experiments, the robot proved highly effective in traversing between wall ledges of the same or different elevations.