Nature Inspired Robotics

Transcription

1 Nature Inspired Robotics

2 Modern Robotics Applications Standard View of robotics involves mainly bipedal robots Simulate Humans (Nature Inspired) BUT Human behaviours are complex Many other types of robotics projects exist To put Nature Inspired Robotics into context, here are 2 standard robotics projects

3 Roomba Robotic Vacuum Cleaner that navigates/cleans intelligently and keeps itself charged Commercially available and has been very successful in clinical trials Many subjects opted to keep Roomba Some became emotionally attached to their new robot Suggests robotics may be accepted into society

4 Roomba (2) Bodes well for robotics projects generally However, this is a relatively simple task See:- Barras, C., 2001, Learning to love to hate robots. New Scientist, 204, 2738, p.22.

5 TUG Small/Medium sized robot used to carry supplies among wards in hospitals Has undergone clinical trials and is being used in hospitals Carries over 200kg, navigates intelligently & communicates with staff & machinery Used for financial reasons

6 TUG (2) Invoked mixed responses Some thought of it as useful & competent Others complained it was overly needy & interrupted them at inappropriate times Highlights that more complex tasks are still beyond modern robotics Still, commercial robots are not excused their shortcomings

7 Smarter Robotics An Intelligent robot should be able to:- Use its powers of perception to notice when a problem solving strategy is required Select the correct strategy for an appropriate problem To otherwise act in response to the needs of those around it without the aid of human intervention

8 Smarter Robotics (2) Software architectures are not available that allow for intelligent responses This requires complex mapping of sensory inputs into appropriate actions Nature inspired techniques such as Artificial Neural Networks (ANNs) and Computer Vision are not yet advanced enough Perception-action of living beings is complex

9 Evolutionary Robotics Evolutionary Systems can be crudely copied in order to evolve random solutions into complex, sophisticated ones Attractive concept (e.g. ANN training) Doubly Nature Inspired Attempting to recreate natural responses Adapting them through evolution Typically involves ANNs repeatedly tuned and tested by evolutionary algorithms

10 Evolutionary Robotics (Case Study) Evolutionary Communicative Behaviour Studying how well robots could be evolved to cooperate in teams, AND, How well they could adapt to competition In the natural world, organisms interact with each other through cues The ones that deal with stimuli best will survive to pass on their genes

11 Evolutionary Robotics It is clear to see that the potential to evolve robot behaviour in this manner exists Furthermore, the objective function can be literally anything In the case of this case study, the objective function was finding and remaining near a food source Initially co-operative, then competitive

12 Evolutionary Robotics Robots displayed blue light, and were capable of detecting it After few generations, they began to associate blue light with food (cooperation) As competition was introduced, robots became uncooperative However, the inference that blue light = food was not dropped by many robots

13 Evolutionary Robotics Advantages Allows evolution of logical behaviour Relatively simple to engineer Complex simulations -> sophisticated robots Disadvantages Does not produce adaptive individuals Not suitable for training commercial robots Undefined behaviour can be dangerous

14 Limitations of Modern Robotics Giving robots co-ordination to walk like a human is very complex Even more challenging is giving it the adaptive behaviour to navigate undefined terrains the way humans do Case Studies: Spring Flamingo Flame

15 Case Study (Spring Flamingo) Focused on creating robot capable of walking on sloped terrain Made 3 important assumptions:- There were that no slipping occurred during the testing The slope caused no variation of the robots gait, and that the terrain sloped only in one direction. The slope was specified as upwards, at an angle parallel to the robots single direction of movement Very limited and inefficient compared to human movement

16 Case Study (Flame) Attempted to replicate human motion in a more sincere manner Used Limit Cycle Walking Walked by effectively falling forwards in a controlled, efficient manner Could navigate 8mm step-downs However, flame cannot walk over rough terrains, navigate stairs or loped surfaces

17 Need for NI Robotics... Modern robots can only navigate simple terrains known at time of design Exploration Navigating across collapsed buildings Animals have had millions of years to adopt novel solutions to this problems Robotics researchers are looking towards nature for inspiration in solving these problems

18 Why use nature as an inspiration? Nature offers engineers new design concepts Biology may provide ideas to make robot behaviour more successful and adaptive Nature s creatures are well adapted to and thrive in the natural world Biology can be viewed as existence proofs as to what robotics might be able to achieve To help advance biological knowledge

19 Why look to nature? Natures creatures are capable of many complex tasks. On Land Walking, Jumping, Running, Climbing In the water Swimming, Diving, Leaping from water In the air Flying, Hovering, Gliding, Diving Anywhere Lifting, Pulling, Grasping

20 How can we use nature as an inspiration? Take inspiration from the whole animal kingdom Biological Locomotion Biomechanics Biological Structures Materials and Geometry Biological Control Sensors and Processing

21 Nature s Designs Animals have been optimised for different things Speed - Cheetah, Falcon Lifting - Elephant, Rhinoceros Beetle Jumping - Kangaroo, Flea, Puma Gliding - Flying Squirrel

22 Capabilities of Nature Stability High manoeuvrability Ability to function in varied environments Movement in a combination of land, water and air Land - walking, running, jumping, climbing Air - flying, gliding, hovering Ability to carry objects many times their own weight

23 Biologically Inspired Structures

24 Biologically Inspired Control

25 Both

26 Insect and Animal Inspired Robot In-depth Examples

27 Goals There were several goals at the onset of this project: Having a robot with a similar physical design to an ant with the ability to walk in any direction (strafe) and rotate at the same time if needed Having a robot capable of navigating uneven and difficult terrain The robot being able to manipulate objects in their environment Power and control autonomous Robots that can cooperatively transport a carried object with another robot ant Capable of communicating with other similar robots wirelessly Relatively inexpensive Performs collective tasks

28 General The BILL-Ant-p robot is divided into three major sections (Fig. 5): Body Legs head/neck Each section is constructed from a 6061 aluminium frame (thickness varying with section) and in. (1.59mm) thick carbon fibre sheets (McMaster-Carr Supply Co., Cleveland, OH, USA). These materials were chosen for their balance of strength and light weight. Figure 1. Acromyrmex versicolor (left, Leafcutter ant found in Arizona, USA, Dale Ward) and BILL- Ant-p (right) body parts.

29 Design Designs were initially created using Autodesk s AutoCAD 14 (Autodesk, Inc., San Rafael, CA, USA). All virtual prototyping for form, placement, range-of motion, and interconnectivity was also done with AutoCAD. Figure 2. BILL-Ant-p robot (without the neck, head, and mandibles)

30 Legs Three degrees-of-freedom were chosen as that is the minimum number which allows strafing; a desired trait for the robot to enable more agile movements. Each leg consists of three joints and four segments (Fig. 3): The first joint is the body-coxa (BC) joint, which swings the coxa forward and rearward in the body s dorsal plane. Next is the coxa-femur (CF) joint, which raises and lowers the femur in the leg-based medial plane. Finally, the femur-tibia (FT) joint raises and lowers the femur and attached foot in the leg-based medial plane. Hobby R/C servos were chosen as joint motors since the motor, transmission, and position controller are contained within the servo package.

31 The design, construction, and control of the joints. Figure 3. Front left leg attached to the body.

32 Legs sensors The foot-mounted force sensors are used to measure the load observed by each foot. These measurements are compiled to determine the total load on the robot, and where that load is centralized. By comparing the amount and location to initial values, changes in the load can be sensed. Since the robot is a raised mass, any perturbations to the robot s head or body will be exerted onto the feet. The shifts in load centre are then used to create active compliance in the robot, where the robot s goal is to remain balanced and stable and will actively retreat from external forces. This allows the robot to take commands from the environment. Figure 4. Foot assembly and force transducer characteristics.

33 Software system A Software Interface was created using Microsoft Visual Basic 6.0. The interface allows the operator to command robot actions and view the robot status. Basic commands on the interface allow the operator to: manipulate each leg joint set foot position in body-centric x-, y-, and z- coordinates initiate a standing-routine; adopt a standing posture adjust body height from the ground; adjust body roll and pitch drive the robot using speed, heading, and rotation values manipulate the neck and mandibles. Figure 5. User interface with Drive Control window shown.

34 Cruise Control In the mid 1970 s Dr. Holk Cruse began research with stick insects to investigate nervous system feedback mechanisms that control leg movement (Cruse 1976; Cruse and Storrer 1977). By the mid 1980 s Dr. Cruse and others (Cruse 1985; Cruse and Müller 1986) were observing leg movements and formulating mechanisms that cause contra-lateral and ipsilateral adjacent legs to influence one another. Figure 7. Cruse s basic rule set for stick insect walking (Schmitz 1998).

35 Robot movements Strafing movements (Fig. 8, centre) allow the robot to move in one direction while facing another. The most extreme example of this is crabbing, where the robot faces forward, but moves sideways. Using basic trigonometry, the x- and y-components of foot movement for each iteration of the walking cycle are determined based on the strafing angle. Walking is considered as strafing with a heading of 0º (forward). Figure 8. Walking (left), strafing at 330º (centre), and CCW rotating (right) foot paths (arrows indicate foot swing direction).

36 Aquapengium Festo Figure1. Nature as a laboratory for efficient processes

37 Bionic penguins Designed as autonomous underwater vehicles (AUVs) that independently orient themselves Navigate through the water basin and develop differentiated, variable behaviour patterns in group operation. New feature in robotics is the torso that can move in any direction. New 3D Fin Ray structure.

38 AquaPengium mechanical solution Figure 2. Wing drive mechanism

39 AquaPengium mechanical solution Figure 3. Rear section as a 3D Fin Ray structure

40 Construction details The kinematics of the penguins underwater flight is imitated almost perfectly. The entire mechanism is designed in such a way that in conjunction with the elastic wing twist. The force provided by one powerful electric motor, whose rotational speed controls the flapping frequency of the wings. The manoeuvres are supported by an intelligent 3D sensor system. To analyse their surroundings, the AquaPenguins fitted with special 3D sonar.

41 List of References [1] Barnes, D. P., Hexapodal Robot Locomotion Over Uneven Terrain, in Proc. IEEE Conf. on Control Applications. Trieste, Italy, pp , September [2] Berns, K., The Walking Machine Catalog: Walking Machine Catalog, World Wide Web, [3] Boggess, M. J., Schroer, R. T., Quinn, R. D., Ritzmann, R. E., Mechanized Cockroach Cruse, H., Müller-Wilm, U., Dean, J., Artificial Neural Nets for Controlling a 6-legged Walking System, in Proc. of the Second International Conference on Simulation of Adaptive Behavior: From Animals to Animats 2, MIT Press, Cambridge, MA, pp , [4] Cruse, H., What Mechanisms Coordinate Leg Movement in Walking Arthropods? Trends in Neurosciences, Vol. 13, pp , [5] Cruse, H., Müller, U., Two Coupling Mechanisms which Determine the Coordination of Ipsilateral Legs in the Walking Crayfish, J. Exp. Biol., Vol. 121, pp , [6] Cruse, H., Coactivating Influences between Neighbouring Legs in Walking Insects, J. Exp. Biol., Vol. 114, pp , 1985 [7] Biologically Inspired Robots, Fred Delcomyn [8] Univeral Leonardo website. [9] Self-Organization, Embodiment, and Biologically Inspired Robotics, Rolf Pfeifer, Max Lungarella and Fumiya Iidal. [10] MIT News, September [11] Barbara Webb s Homepage.

42 References Continued [12] Robot Phonotaxis in the Wild: a Biologically Inspired Approach to Outdoor Sound Localisation. A.D. Horchler, R.E. Reeve, B.H. Webb, R.D. Quinn [13] New neural circuits for robot phonotaxis. Richard E. Reeve and Barbara H. Webb [14] Robots, crickets and ants: models of neural control of chemotaxis and phonotaxis. Barbara Webb [15] Rationale behind Biological Inspiration in Robot Design, Satyandra K. Gupta