This paper introduces Bruce, the CSIRO Dynamic Hexapod Robot capable of autonomous, dynamic locomotion over difficult terrain. This robot is built around Apptronik linear series elastic actuators, and went from design to deployment in under a year by using approximately 80\% 3D printed structural (joints and link) parts. The robot has so far demonstrated rough terrain traversal over grass, rocks and rubble at 0.3m/s, and flat-ground speeds up to 0.5m/s. This was achieved with a simple controller, inspired by RHex, with a central pattern generator, task-frame impedance control for individual legs and no foot contact detection. The robot is designed to move at up to 1.0m/s on flat ground with appropriate control, and was deployed into the the DARPA SubT Challenge Tunnel circuit event in August 2019.
Bio-inspired walking hexapod robots are a relatively young branch in robotics in both state of the art and applications. Despite their high degree of flexibility and adaptability derived by their redundant design, the research field that compliments their abilities is still very lacking. In this paper will be proposed state-of-the-art hexapod robot specific control architecture that allows for full control over robot speed, body orientation and walk gait type to employ. Furthermore terrain interaction will be deeply investigated, leading to the development of a terrain-adapting control algorit…
CSIRO（联邦科学与工业研究组织）；University of Technology Sydney（悉尼科技大学）；University of Queensland（昆士兰大学）
Legged robots traversing in confined environments could find their only path is blocked by obstacles. In circumstances where the obstacles are movable, a multilegged robot can manipulate the obstacles using its legs to allow it to continue on its path. We present a method for a hexapod robot to autonomously generate manipulation trajectories for detected obstacles. Using a RGB-D sensor as input, the obstacle is extracted from the environment and filtered to provide key contact points for the manipulation algorithm to calculate a trajectory to move the obstacle out of the path. Experiments on a…
This paper introduces a six-legged autonomous robot managed by a single controller and a software core modeled on subsumption architecture. We begin by discussing the features and capabilities of IsoPod, a new processor for robotics which has enabled a streamlined implementation of our project. We argue that this processor offers a unique set of hardware and software features, making it a practical development platform for robotics in general and for subsumption-based control architectures in particular. Next, we summarize original ideas on subsumption architecture implementation for a six-leg…
Modern climbing robots have risen to great heights, but mechanisms meant to scale cliffs often locomote slowly and over-cautiously on level ground. Here we introduce T-RHex, an iteration on the classic cockroach-inspired hexapod that has been augmented with microspine feet for climbing. T-RHex is a mechanically intelligent platform capable of efficient locomotion on ground with added climbing abilities. The legs integrate the compliance required for the microspines with the compliance required for locomotion in order to simplify the design and reduce mass. The microspine fabrication is simplif…
Model-based thermal drift compensation for high-precision hexapod robot actuators
LIRMM (Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier)（蒙彼利埃计算机、机器人与微电子实验室）；Montpellier Univ.（蒙彼利埃大学）；CNRS（法国国家科学研究中心）；SYMETRIE（SYMETRIE公司）；LCM (Laboratoire Commun de Métrologie)（计量联合实验室）；LNE（法国国家计量测试实验室）；CNAM（法国国立工艺学院）
Berkeley Sensor & Actuator Center（伯克利传感器与执行器中心）；University of California, Berkeley（加州大学伯克利分校）
Robots and control systems rely upon precise timing of sensors and actuators in order to operate intelligently. We present a functioning hexapod robot that walks with a dual tripod gait; each tripod is actuated using its own local controller running on a separate wireless node. We compare and report the results of operating the robot using two different decentralized control schemes. With the first scheme, each controller relies on its own local clock to generate control signals for the tripod it controls. With the second scheme, each controller relies on a variable that is local to itself but…
Shandong University（山东大学）；The School of Control Science and Engineering (CSE) of Shandong University（山东大学控制科学与工程学院）
Dynamic target detection and target tracking are hot issues in the field of image. In order to explore its application value in the field of mobile robot, a dynamic target detection and tracking system is designed based on hexapod robot. Firstly, the dynamic target detection method is introduced with region merging and adaptive external point filtering based on motion compensation method. This method achieves the accurate compensation of the moving background through symmetric matching and adaptive external point filtering, and achieves complete detection of non-rigid objects by region merging…
International Institute of Information Technology Bangalore（班加罗尔国际信息技术学院）
Developing a framework for the locomotion of a six-legged robot or a hexapod is a complex task that has extensive hardware and computational requirements. In this paper, we present a bio-inspired framework for the locomotion of a hexapod. Our locomotion model draws inspiration from the structure of a cockroach, with its fairly simple central nervous system, and results in our model being computationally inexpensive with simpler control mechanisms. We consider the limb morphology for a hexapod, the corresponding central pattern generators for its limbs, and the inter-limb coordination required …
Optimizing gait stability for legged robots is a difficult problem. Even on level surfaces, effectively traversing across different textures (e.g., carpet) rests on dynamically tuning parameters in multidimensional space. Inspired by biology, evolutionary algorithms (EA) remain an attractive solution for feasibly implementing robotic locomotion with both energetic economy and rapid parameter convergence. Here, we leveraged this class of algorithms to evolve a stable hexapod gait controller capable of traversing uneven terrain and obstacles. Gait parameters were evolved in a rigid body dynamics…
HeLoM: Hierarchical Learning for Whole-Body Loco-Manipulation by a Hexapod Robot
MARMoT Lab, Department of Mechanical Engineering, National University of Singapore（机械工程系，新加坡国立大学MARMoT实验室）；Center for X-mechanics, Zhejiang University（浙江大学X力学中心）
Middle East Technical University（中东技术大学）；Robotics and Artificial Intelligence Technologies Application and Research Center（机器人与人工智能技术应用研究中心）
Underactuated legged robots depict highly nonlinear and complex dynamical behaviors that create significant challenges in accurately modeling system dynamics using both first principles and system identification approaches. Hence, it makes a more substantial challenge to design stabilizing controllers. If physical parameters on mathematical models have miscalibrations due to uncertainty in identifying and modeling processes, designed controllers could perform poorly or even result in unstable responses. Moreover, these parameters can certainly change-over-time due to operation and environmenta…
Locomotion is a crucial challenge for legged robots that is addressed "effortlessly" by biological networks abundant in nature, named central pattern generators (CPG). The multitude of CPG network models that have so far become biomimetic robotic controllers is not applicable to the emerging neuromorphic hardware, depriving mobile robots of a robust walking mechanism that would result in inherently energy-efficient systems. Here, we propose a brain-morphic CPG controler based on a comprehensive spiking neural-astrocytic network that generates two gait patterns for a hexapod robot. Building on …
Bielefeld University（比勒费尔德大学）；Leibniz Institute for Neurobiology（莱布尼茨神经生物学研究所）；Otto-von-Guericke University（奥托·冯·格里克大学）
Locomotion is a prime example for adaptive behavior in animals and biological control principles have inspired control architectures for legged robots. While machine learning has been successfully applied to many tasks in recent years, Deep Reinforcement Learning approaches still appear to struggle when applied to real world robots in continuous control tasks and in particular do not appear as robust solutions that can handle uncertainties well. Therefore, there is a new interest in incorporating biological principles into such learning architectures. While inducing a hierarchical organization…
Leg-Arm Coordinated Operation for Curtain Wall Installation
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；Shenzhen University of Advanced Technology and University of Chinese Academy of Sciences（深圳先进技术大学和中国科学院大学）
Learning how to walk is a sophisticated neurological task for most animals. In order to walk, the brain must synthesize multiple cortices, neural circuits, and diverse sensory inputs. Some animals, like humans, imitate surrounding individuals to speed up their learning. When humans watch their peers, visual data is processed through a visual cortex in the brain. This complex problem of imitation-based learning forms associations between visual data and muscle actuation through Central Pattern Generation (CPG). Reproducing this imitation phenomenon on low power, energy-constrained robots that a…
Learning to walk -- i.e., learning locomotion under performance and energy constraints continues to be a challenge in legged robotics. Methods such as stochastic gradient, deep reinforcement learning (RL) have been explored for bipeds, quadrupeds and hexapods. These techniques are computationally intensive and often prohibitive for edge applications. These methods rely on complex sensors and pre-processing of data, which further increases energy and latency. Recent advances in spiking neural networks (SNNs) promise a significant reduction in computing owing to the sparse firing of neuros and h…
This work introduces a novel technique for fabricating functional robots using 3D printers. Simultaneously depositing photopolymers and a non-curing liquid allows complex, pre-filled fluidic channels to be fabricated. This new printing capability enables complex hydraulically actuated robots and robotic components to be automatically built, with no assembly required. The technique is showcased by printing linear bellows actuators, gear pumps, soft grippers and a hexapod robot, using a commercially-available 3D printer. We detail the steps required to modify the printer and describe the design …
Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO)（澳大利亚联邦科学与工业研究组织数据61分部）；Queensland University of Technology（昆士兰科技大学）；University of Queensland（昆士兰大学）
We compare two representations used to define the morphology of legs for a hexapod robot, which are subsequently 3D printed. A leg morphology occupies a set of voxels in a voxel grid. One method, a direct representation, uses a collection of Bezier splines. The second, an indirect method, utilises CPPN-NEAT. In our first experiment, we investigate two strategies to post-process the CPPN output and ensure leg length constraints are met. The first uses an adaptive threshold on the output neuron, the second, previously reported in the literature, scales the largest generated artefact to our desir…
Seoul National University（首尔国立大学）；Georgia Institute of Technology（佐治亚理工学院）
A motion-based control interface promises flexible robot operations in dangerous environments by combining user intuitions with the robot's motor capabilities. However, designing a motion interface for non-humanoid robots, such as quadrupeds or hexapods, is not straightforward because different dynamics and control strategies govern their movements. We propose a novel motion control system that allows a human user to operate various motor tasks seamlessly on a quadrupedal robot. We first retarget the captured human motion into the corresponding robot motion with proper semantics using supervis…
The University of Southern Denmark（南丹麦大学）；Vidyasirimedhi Institute of Science and Technology（维迪亚西里梅迪科技学院）
Legged robots have significant potential to operate in highly unstructured environments. The design of locomotion control is, however, still challenging. Currently, controllers must be either manually designed for specific robots and tasks, or automatically designed via machine learning methods that require long training times and yield large opaque controllers. Drawing inspiration from animal locomotion, we propose a simple yet versatile modular neural control structure with fast learning. The key advantages of our approach are that behavior-specific control modules can be added incrementally…
Georgia Institute of Technology（佐治亚理工学院）；Facebook AI Research（Facebook人工智能研究院）
Recent work has shown results on learning navigation policies for idealized cylinder agents in simulation and transferring them to real wheeled robots. Deploying such navigation policies on legged robots can be challenging due to their complex dynamics, and the large dynamical difference between cylinder agents and legged systems. In this work, we learn hierarchical navigation policies that account for the low-level dynamics of legged robots, such as maximum speed, slipping, contacts, and learn to successfully navigate cluttered indoor environments. To enable transfer of policies learned in si…
An Interpretable Neural Control Network with Adaptable Online Learning for Sample Efficient Robot Locomotion Learning
Vidyasirimedhi Institute of Science and Technology（维达亚希米德科学与技术学院）；The Mærsk Mc-Kinney Møller Institute（马士基麦金尼·莫勒研究所）；University of Southern Denmark（南方丹麦大学）
The University of Queensland（昆士兰大学）；Commonwealth Scientific and Industrial Research Organisation (CSIRO)（联邦科学与工业研究组织（CSIRO））
Multilegged robots have the ability to perform stable locomotion on relatively rough terrain. However, the complexity of legged robots over wheeled or tracked robots make them difficult to control. This paper presents OpenSHC (Open-source Syropod High-level Controller), a versatile high-level controller {capable of generating gaits and poses for quasi-static multilegged robots, both simulated and with real hardware implementations. With full Robot Operating System (ROS) integration, the controller can be quickly deployed on robots with different actuators and sensor payloads}. The flexibility …
Carnegie Mellon University（卡内基梅隆大学）；Chinese Academy of Sciences（中国科学院）；Lebanese University（黎巴嫩大学）
Recent literature in the robotics community has focused on learning robot behaviors that abstract out lower-level details of robot control. To fully leverage the efficacy of such behaviors, it is necessary to select and sequence them to achieve a given task. In this paper, we present an approach to both learn and sequence robot behaviors, applied to the problem of visual navigation of mobile robots. We construct a layered representation of control policies composed of low- level behaviors and a meta-level policy. The low-level behaviors enable the robot to locomote in a particular environment …
Many robot manipulation skills can be represented with deterministic characteristics and there exist efficient techniques for learning parameterized motor plans for those skills. However, one of the active research challenge still remains to sustain manipulation capabilities in situation of a mechanical failure. Ideally, like biological creatures, a robotic agent should be able to reconfigure its control policy by adapting to dynamic adversaries. In this paper, we propose a method that allows an agent to survive in a situation of mechanical loss, and adaptively learn manipulation with compromi…
Carnegie Mellon University（卡内基梅隆大学）；The Hong Kong Polytechnic University（香港理工大学）
State-of-the-art distributed algorithms for reinforcement learning rely on multiple independent agents, which simultaneously learn in parallel environments while asynchronously updating a common, shared policy. Moreover, decentralized control architectures (e.g., CPGs) can coordinate spatially distributed portions of an articulated robot to achieve system-level objectives. In this work, we investigate the relationship between distributed learning and decentralized control by learning decentralized control policies for the locomotion of articulated robots in challenging environments. To this en…
GPO: Growing Policy Optimization for Legged Robot Locomotion and Whole-Body Control
Beihang University, China（北京航空航天大学）；Department of Mechanical Engineering, National University of Singapore, Singapore（新加坡国立大学机械工程系）；Henan Univeristy, China（河南大学）
Robot footstep planning strategies can be divided in two main approaches: discrete searches and continuous optimizations. While discrete searches have been broadly applied, continuous optimizations approaches have been restricted for humanoid platforms. This article introduces a generalized continuous-optimization approach for multilegged footstep planning which can be adapted to different platforms, regardless the number and geometry of legs. This approach leverages Mixed-Integer Convex Programming to account for the non-convex constraints that represent footstep rotation and obstacle avoidan…
Southern University of Science and Technology（南方科技大学）
This article presents the design, implementation, and performance evaluation of SWheg, a novel modular wheel-leg transformable robot family with minimalist actuator realization. SWheg takes advantage of both wheeled and legged locomotion by seamlessly integrating them on a single platform. In contrast to other designs that use multiple actuators, SWheg uses only one actuator to drive the transformation of all the wheel-leg modules in sync. This means an N-legged SWheg robot requires only N+1 actuators, which can significantly reduce the cost and malfunction rate of the platform. The tendon-dri…
Modular robots can be rearranged into a new design, perhaps each day, to handle a wide variety of tasks by forming a customized robot for each new task. However, reconfiguring just the mechanism is not sufficient: each design also requires its own unique control policy. One could craft a policy from scratch for each new design, but such an approach is not scalable, especially given the large number of designs that can be generated from even a small set of modules. Instead, we create a modular policy framework where the policy structure is conditioned on the hardware arrangement, and use just o…
Fast and Modular Whole-Body Lagrangian Dynamics of Legged Robots with Changing Morphology
Autonomous Space Robotics and Mechatronics Laboratory, Carleton University（自主空间机器人与机电实验室，卡尔顿大学）；Mechanical, Industrial, and Mechatronics Engineering Department, Toronto Metropolitan University（机械、工业与机电工程系，多伦多 Metropolitan 大学）
Central to the design of many robot systems and their controllers is solving a constrained blackbox optimization problem. This paper presents CNMA, a new method of solving this problem that is conservative in the number of potentially expensive blackbox function evaluations; allows specifying complex, even recursive constraints directly rather than as hard-to-design penalty or barrier functions; and is resilient to the non-termination of function evaluations. CNMA leverages the ability of neural networks to approximate any continuous function, their transformation into equivalent mixed integer…
KTH Royal Institute of Technology（KTH皇家理工学院）；Facebook AI Research（脸书人工智能研究院）
Data-efficiency is crucial for autonomous robots to adapt to new tasks and environments. In this work we focus on robotics problems with a budget of only 10-20 trials. This is a very challenging setting even for data-efficient approaches like Bayesian optimization (BO), especially when optimizing higher-dimensional controllers. Simulated trajectories can be used to construct informed kernels for BO. However, previous work employed supervised ways of extracting low-dimensional features for these. We propose a model and architecture for a sequential variational autoencoder that embeds the space …
The design of gaits for robot locomotion can be a daunting process which requires significant expert knowledge and engineering. This process is even more challenging for robots that do not have an accurate physical model, such as compliant or micro-scale robots. Data-driven gait optimization provides an automated alternative to analytical gait design. In this paper, we propose a novel approach to efficiently learn a wide range of locomotion tasks with walking robots. This approach formalizes locomotion as a contextual policy search task to collect data, and subsequently uses that data to learn…
One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion
Department of Computer Science, Technical University of Darmstadt（德累斯顿技术大学计算机科学系）；Institute of Robotics and Machine Intelligence, Poznan University of Technology（波兹南技术大学机器人与机器智能研究所）；German Research Center for AI (DFKI), Research Department: Systems AI for Robot Learning（德国人工智能研究中心（DFKI）系统AI for机器人学习研究部）；IDEAS NCBR, Warsaw, Poland（华沙波兰IDEAS NCBR）；Centre for Cognitive Science（认知科学中心）
Beijing University of Aeronautics and Astronautics（北京航空航天大学）；Bernstein Center for Computational Neuroscience（伯恩斯坦计算神经科学中心）；Georg-August-Universität Göttingen（哥廷根大学）；University of Southern Denmark（南丹麦大学）
An originally chaotic system can be controlled into various periodic dynamics. When it is implemented into a legged robot's locomotion control as a central pattern generator (CPG), sophisticated gait patterns arise so that the robot can perform various walking behaviors. However, such a single chaotic CPG controller has difficulties dealing with leg malfunction. Specifically, in the scenarios presented here, its movement permanently deviates from the desired trajectory. To address this problem, we extend the single chaotic CPG to multiple CPGs with learning. The learning mechanism is based on …
Agile asymmetric multi-legged locomotion: contact planning via geometric mechanics and spin model duality
Department of Mechanical Engineering, Pennsylvania State University（宾夕法尼亚州立大学机械工程系）；MIT Improbable AI Lab, Maschusetts Institute of Technology（麻省理工学院Improbable AI实验室）；Department of Physics, Georgia Institute of Technology（佐治亚理工学院物理系）；Department of Physics, Tsinghua University（清华大学物理系）
