Drawing inspiration from nature, legged robots are capable of traversing unstructured terrain inaccessible to most wheeled and tracked robots. They provide a means for observing remote environments, inspecting confined spaces, assisting first responders in the aftermath of disasters as well as tending to our crop fields of the future.
What do we do?
At CSIRO, we use our fleet of Syropods (CSIRO hexapod robots) to develop component techniques and capabilities required by robots to perform real-world missions. These missions range from inspecting confined spaces in the manufacturing industry, traversing, sensing and monitoring unstructured terrain (eg. collapsed buildings/mines, rainforests). These environments are typically hazardous for humans to operate in. Legged robots have an advantage over wheeled counterparts in being able to climb over obstacles and not disturb the surface in the process. Other potential applications would be in agriculture where fleets of autonomous legged robots can do crop monitoring and management without compacting the soil and damaging the crop.
Some of CSIRO’s six-legged Syropods in outdoor environments
Proprioceptive control of an over-actuated hexapod robot
We introduce a novel hexapod robot, Weaver, which has five joints per leg and 30 degrees of freedom overall. The two redundant joints improve the locomotion of the robot by controlling the body pose and the leg orientation with respect to the ground. The indirect force controller reacts to unstructured terrain and achieves self-stabilizing behavior without prior profiling of the terrain through exterioceptive sensing. Instead of adding force sensors, the force is calculated by processing the torque output of the actuators. We experimentally evaluate Weaver with the proposed controller and demonstrate that it can effectively traverse challenging terrains and high gradient slopes, reduce angular movements of the body by more than 55% and reduce the cost of transport (up to 50% on uneven terrain and by 85% on a slope with 20°). The controller also enables Weaver to walk up inclines of up to 30\,\degree, and remain statically stable on inclines up to 50°.
Terrain-dependent motion adaptation for hexapod robots
The ability to traverse uneven terrain is one of the key advantages of legged robots. However, their effectiveness relies on selecting appropriate gait parameters such as duty factor, stride height and joint stiffness. We present a novel terrain sensing method using stereo vision that can inform gait parameter selection for a legged robot. This method is evaluated using a hexapod robot with 30 degrees of freedom. The stride height and joint stiffness are adapted based on inputs from the vision system allowing the robot to effectively traverse variable rough terrain. Experiments show, that adaptive motion parameters lead to efficient locomotion both in terms of energy consumption and mission success.
Energetics based gait switching
Legged robots can use many different walking pattern or gaits for locomotion. Each of these gaits has different properties such as speed, energy consumption and ground traction. Different terrains and different mission objectives require appropriate gaits to maintain traversal efficiency. Consequently, as a legged robot transitions from one type of terrain to another, the gait pattern should be adapted so as to maximise traction and energy efficiency. One of our research threads explores the use of power consumption as estimated by the robot in real-time for guiding this gait transition. We have developed a technique where the robot autonomously assesses its power consumption, relates it to the traction, and switches between gaits to maintain traversal efficiency. We have tested this approach on a hexapod robot traversing a variety of terrain types and stiffness, including concrete, grass, mulch and leaf litter. Our results show that gait switching on energetics alone enables traction maintenance and efficient locomotion across different terrains.
Stabilisation in unstructured terrain
Being able to detect leg slips and recover from them is an important aspect of navigating in rough and unstructured terrain. When the terrain is either well known ahead of time (accurate terrain model known a priori) or is accurately observed by on-board sensors, motion planning algorithms can be used by the robot for navigation and maintaining stability. However, unexpected leg disturbances could occur due to inadequacies in the terrain model or sensors or simply due to the dynamic nature of the terrain (eg. loose soil/rocks, debris, sand).
We have developed a state space based framework for stabilisation of a high dimensional multi-legged robot which detects and recovers from unexpected events such as leg slip. We have tested this approach using a hexapod robot with extended limbs. Our results show that roll and pitch stability is improved significantly when using this method.
Ground cover classification (Joint feedback based)
The effectiveness of a legged robot’s gait is highly dependent on the terrain the robot is traversing. It is therefore advantageous for a legged robot to adapt its behaviour to suit the environment. To achieve this, the robot must be able to detect and classify the type of ground cover it is traversing. We have developed a novel approach for ground cover classification that use the differences between commanded and actual positions of each leg joint. We have implemented and successfully tested our method on many different terrain types.
Ground cover classification (Acoustics based)
Legged robots offer a more versatile solution to traversing outdoor uneven terrain compared to their wheeled and tracked counterparts. They also provide a unique opportunity to perceive the terrain-robot interactions by listening to the sounds generated during locomotion. Legged robots such as hexapod robots produce rich acoustic information for each gait cycle which includes the foot fall sounds and feet pushing on the terrain (support phase), as well as the sounds produced when the feet travel through the air (stride phase). Interpreting this information to perceive the terrain it is traversing makes available another valuable sensing modality which can feed in to higher level systems to facilitate robust and efficient navigation through unknown terrain. We have implemented an online real- time terrain classification system for legged robots that utilise features from the acoustic signals produced during locomotion. The system was trained on 7 different terrain types and the results of the experimental evaluations show a true positive rate of up to 95.1.
Evolutionary approaches for legged robot control
Due to their morphologies, legged robots are ideal platforms for investigating biologically-inspired approaches to control and navigation. We are currently investigating the application of evolutionary/machine learning techniques to generate task-specific and platform-specific controllers, targeting improved performance. As an example, depending on the control system, variation of joint controller gain values provide a way to decrease energy consumption during operation. We present a fully automated hardware optimisation test-bed that use Evolutionary Algorithms to find a optimal set of controller parameters that increase locomotion performance.
Legged robots with compliant joints
We are using elastic joints to make our legged robots highly flexible. This means they interact softly with people, with the ground and with equipment that they come in contact with. This helps the robots negotiate uneven and unstable terrain as well as to absorb the impact of falls. These attributes make it ideal for disaster recovery, remote exploration and for consumer use.
Motion planning for legged robots
Legged robots such as hexapods are highly flexible robotic platforms due to their high degrees of freedom. However the high degrees of freedom also introduce challenges in navigation and control especially in complex environments like rocky terrains, soft soil, in confined spaces etc. We are actively researching on state of the art motion planning techniques to enable stable sensor payload navigation through these complex terrains.
Outdoor mapping with a legged robot
Confined inspection with a legged robot
Detection and recovery from multiple leg slip
Channel 10 - Scope episode on Biomimicry
Channel 9 News - CONNECT Expo 2015
Bjelonic, M., Kottege, N., & Beckerle, P. (2016), Proprioceptive Control of an Over-Actuated Hexapod Robot in Unstructured Terrain, To appear in proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016).
Homberger, T., Bjelonic, M., Kottege, N., & Borges, P. (2016), Terrain-Dependant Motion Adaptation for Hexapod Robots, To appear in proceedings of the International Symposium on Experimental Robotics (ISER 2016).
Christie, J., & Kottege, N. (2016), Acoustics based Terrain Classification for Legged Robots. In proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2016), Stockholm, Sweden, May, 2016
Kottege, N., Parkinson, C., Moghadam, P., Elfes, A., & Singh, S. P. N. (2015), Energetics-Informed Hexapod Gait Transitions, In proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2015), Seattle, WA, USA, May 2015
Hoerger, M., Kottege, N., Bandyopadhyay, T., Moghadam, P., & Elfes, A. (2014), Real-time Stabilisation for Hexapod Robots, In proceedings of the International Symposium on Experimental Robotics (ISER 2014), Marrakesh, Morocco, June 2014
Best, G., Moghadam, P., Kottege, N., & Kleeman, L. (2013), Terrain Classification Using a Hexapod Robot. In proceedings of the Australasian Conference on Robotics and Automation (ACRA 2013), Sydney, Australia, December 2013
Syropods on different types of terrain