Legged robots require low-inertia limbs capable of carrying a high payload. The design of such limbs poses challenges in integrating optimal kinematic structures with practical design considerations. In the search for optimal design parameters, advantages of optimization algorithms can be applied. This paper introduces an open-source framework for optimizing topology and parameters of closed linkage mechanisms, addressing the need for task-specific robotic limbs. Closed-loop structures are motivated by two main purposes: (1) to decrease robotic limb inertia by relocation of actuators close to the robot’s body and (2) to redistribute efforts among actuators. The framework leverages joint-based spatial graph representations, kinetostatic criteria, and multi-objective genetic algorithms to optimize mechanism topology and parameters. Focusing on kinetostatic criteria such as Jacobian metrics and inertia properties, the framework swiftly explores the design space to balance trade-offs in robot linkages. We demonstrate the framework pipeline for the task of optimizing planar robotic legs with 2 degrees of freedom. Project github page: https://licaibeerlab.github.io/jmoves.github.io/

This paper describes a novel parametric optimization procedure for three flexure cross hinges (TFCH) integrated into multi-link leg mechanisms with closed-loop kinematics. Despite advantages such as compliance, no need for joint lubrication, light weight and cost-efficiency, such shaftless mechanisms have not been widely used, especially in the field of dynamic locomotion, also because their design is challenging and barely studied. Using a morphological computation approach, we have optimized the TFCH geometry to achieve the desired joint stiffness using frequency analysis, ensuring safe and stable hopping under external perturbations. We combined rigid body dynamics with lumped stiffness model and finite element modeling using the SPACAR toolbox to simulate various designs within our optimization pipeline. To illustrate the efficiency of the resulting designs, we built a prototype and conducted a series of full-scale experiments with ramp jumps whose trajectories were recorded by a motion capture system. The experiments showed that TFCH can be effectively integrated into leg mechanisms, providing benefits such as impact robustness, energy recuperation, and the ability to work in extreme conditions.

The design process of robotic systems is a complex journey that involves multiple phases. Throughout this process, the aim is to tackle various criteria simultaneously, even though they often contradict each other. The ultimate goal is to uncover the optimal solution that resolves these conflicting factors. Within this paper we propose a design methodology to generate linkage mechanisms for robots with morphological computation. We use a graph grammar and a heuristic search algorithm to create robot mechanism graphs that are converted into simulation models for testing the design output. To verify the design methodology we have applied it to a relatively simple quasi-static problem of object grasping. Designing a fully actuated gripper may seem simple, but we found a way to automatically design an underactuated tendon-driven gripper that can grasp a wide range of objects. This is possible because of its structure, not because of sophisticated planning or learning. To test the applicability of the proposed method in real engineering practice, we used it to create physical prototypes. Simulation results together with results of testing of physical prototypes are given at the end of the paper. The framework is open source and the link to GitHub is given in the paper.

The main advantages of legged robots over wheeled ones are their abilities to traverse on uneven terrain due to the use of intermittent contacts and an ability to shift the center of mass relative to the contact location. A robot's leg design can be implemented by using an open-chain mechanism actuated with high-density torque actuators though this solution needs a vast energy budget. An alternative way to design a leg mechanism is the application of morphological computation principle. According to the principle, most of the desired robot's behavior can be delegated to the mechanics with minimum control effort needed to excite, stabilize or augment it. Within this paper, we have proposed a method to synthesize a leg for hopping robots. Due to optimization of mechanical structure, geometric parameters, mass distribution, and elasticity allocation, our method allows getting an energy-efficient robot with minimal control system complexity, which is accomplished via series elastic allocation and active variable length link. Based on this approach, we have designed a hopping robot with two low performance actuators that can achieve hopping, running, and, in the case of a biped or quadruped robot, walking motion. The paper describes a synthesized leg linkage and overviews prototype design, control strategy, and test results of a physical prototype.

Designing robots is a multiphase process aimed at solving a multi-criteria optimization problem to find the best possible detailed design. Generative design (GD) aims to accelerate the design process compared to manual design, since GD allows exploring and exploiting the vast design space more efficiently. In the field of robotics, however, relevant research focuses mostly on the generation of fully-actuated open chain kinematics, which is trivial in mechanical engineering perspective. Within this paper, we address the problem of generative design of closed-chain linkage mechanisms. A GD algorithm has to be able to generate meaningful mechanisms which satisfy conditions of existence. We propose an optimization-driven algorithm for generation of planar closed-chain linkages to follow a predefined trajectory. The algorithm creates an unlimited range of physically reproducible design alternatives that can be further tested in simulation. These tests could be done in order to find solutions that satisfy extra criteria, e.g., desired dynamic behavior or low energy consumption. The proposed algorithm is called “respawn” since it builds a new linkage after the ancestor has been tested in a virtual environment in pursuit for the optimal solution. To show that the algorithm is general enough, we show a set of generated linkages that can be used for a wide class of robots.

Anthropomorphic robotic grippers are required for robots, prostheses, and orthosis to enable manipulation of a priori unknown and variable-shape objects. It has to meet a wide range of sometimes contradictory requirements in terms of adaptivity, dexterity, high payload to weight ratio, robustness, aesthetics, compactness, lightweight, etc. Within this paper, we utilize the morphological computation approach to introduce design for anthropomorphic re-configurable underactuated grippers. The key to fingers' adaptivity is embedded passive variable length links and elastic elements at input joints. Based on this concept, we designed a palm-size five-finger gripper, where 14 DoFs, including thumb, are controlled by just 4 motors, such that it can perform both precision pinch and encompassing power grasps of various objects. The paper describes synthesized linkages for digits, hand design overview, control strategy, and test results of a physical prototype.

We present an optimization-based structural-parametric synthesis method for reconfigurable closed-chain underactuated linkages for robotic systems that physically interact with the environment with an emphasis on adaptive grasping. The key idea is to implement morphological computation concepts to keep both necessary trajectory-specific holonomic constraints and mechanism adaptivity using variable length links (VLL), while we evolve from a fully actuated to an underactuated system satisfying imposed design requirements. It allows to minimize the number of actuators, weight, and cost but keep high payload and endurance that are not reachable by tendon-driven designs. Despite the method is general enough, for clarity, we demonstrate its use on a number of finger mechanisms for adaptive grippers.

One way to create a quadruped galloping robot from scratch is to design a brick-shaped body and utilize relatively simple open-chain leg mechanisms controlled with relatively complex control algorithms. Alternatively, we can look at how nature solved the same task designing fast mammals such as cheetah, and by means of morphological computation, we can design a complex mechanical system that has much of the desired behavior within inherent dynamics and only a little control effort is needed to stabilize or augment the motion.In this paper, we have analyzed a real cheetah motion using video tracking and looked for a way to match the dynamic model parameters of the real cheetah with a galloping robot with an elastic spine. We believe the elastic spine is the essential feature for a fast-running energy-efficient galloping robot. Within this paper, we are focused on the flying stage when the elastic spine affects the motion of the robot’s front and rear bodies. We have found how to optimize mass distribution and elasticity in the spine in order to get the cheetah-like galloping motion of a quadruped robot.

Practical identifiability of Systems Biology models has received a lot of attention in recent scientific research. It addresses the crucial question for models' predictability: how accurately can the models' parameters be recovered from available experimental data. The methods based on profile likelihood are among the most reliable methods of practical identification. However, these methods are often computationally demanding or lead to inaccurate estimations of parameters' confidence intervals. Development of methods, which can accurately produce parameters' confidence intervals in reasonable computational time, is of utmost importance for Systems Biology and QSP modeling. We propose an algorithm Confidence Intervals by Constraint Optimization (CICO) based on profile likelihood, designed to speed-up confidence intervals estimation and reduce computational cost. The numerical implementation of the algorithm includes settings to control the accuracy of confidence intervals estimates. The algorithm was tested on a number of Systems Biology models, including Taxol treatment model and STAT5 Dimerization model, discussed in the current article. The CICO algorithm is implemented in a software package freely available in Julia (https://github.com/insysbio/LikelihoodProfiler.jl) and Python (https://github.com/insysbio/LikelihoodProfiler.py).

The biomimetic approach in robotics is promising: nature has found many good solutions through millions of years of evolution. However, creating a design that enables fast and energy-efficient locomotion remains a major challenge. This paper focuses on the development of a full leg mechanism for a fast and energy-efficient 4-legged robot inspired by a cheetah morphology. In particular, we analyze how the allocation of flexible elements and their stiffness affects the cost of transport and peak power characteristics for vertical jumps and a galloping motion. The study includes the femur and full leg mechanism's locomotory behavior simulation, capturing its interaction with the ground.

This paper describes the design of a gripper device for handling heavy steel tubes with variable physical properties such as diameter, mass and length. This grasping device represents an alternative solution to expensive and sophisticated anthropomorphic grippers. This research is focused on hardware design and concept issues. The designed device for assistive robotic applications can represent a hardware component of an industrial cyber-physical system. Design of such tools is extremely relevant for modern industry and science. Research work, mechanical design and implementation steps are described in the paper in details. Testing procedures and corresponding illustrative results are also reported.

The results of the work on the creation of a hand rehabilitation complex with given mass-size characteristics and various training regimes are presented. A brief description of the three versions of the mechanical part of the rehabilitation device is given. A simplified device control scheme is presented, a brief description of the training modes is given, additional modules that expand the functional are described. Brief conclusions on the work were done, as well as the prospects for the development of the project were outlined.