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Company
Portfolio Data
Back to Company SearchSQUISHY ROBOTICS INC
UEI: HUB4QU2MDE14
Number of Employees: 6
HUBZone Owned: Yes
Woman Owned: Yes
Socially and Economically Disadvantaged: No
SBIR/STTR Involvement
Year of first award: 2018
2
Phase I Awards
1
Phase II Awards
50%
Conversion Rate
$332,999
Phase I Dollars
$733,898
Phase II Dollars
$1,066,897
Total Awarded
Awards
Autonomous Deployment of Sensors through Airdrop Operations by Squishy Robotics
Amount: $107,999 Topic: A19-062
This proposal advances autonomous deployment of sensors through airdrop operations by leveraging Tensegrity Robotics. These robots have a unique outer tension-integrity structure that can be deployed from aerial vehicles. These structures decrease a payload’s terminal velocity and provides impact protection, thus eliminating the need for a parachute. This combination of features is particularly attractive for autonomous sensor deployment because they enable immediate sensor operation upon landing. Squishy Robotics has developed a Tensegrity Robot for improved situational awareness in CBRNE (Chemical, Biological, Radiological, Nuclear, Explosive) situations. This NASA-based technology is capable of airdropping 1 lb payloads via drone, and has been bench and field tested. We propose to build a scaled-up version of this platform by 1) running simulations to optimize components and parameters to produce a design to carry 50 lbs, 2) building and testing a proof-of-concept platform capable of carrying 5 lbs, 3) controlling orientation upon landing, and 4) validating materials which are fundamentally new to the airdrop community. Beyond the military applications, an uprated Tensegrity Robot is commercially attractive, because it opens the possibility to airdrop currently manufactured 3rd party sensors, thus increasing the number of potential use cases for airdropping of remote sensors.
Tagged as:
SBIR
Phase I
2019
DOD
ARMY
SBIR Phase II: Rapidly Deployable Mobile Sensor Robots for Disaster Response and Monitoring
Amount: $733,898 Topic: EW
The broader impact/commercial potential of this project is to commercialize previous research in tensegrity robots for new markets in disaster response. Future deaths and injuries of both victims and first responders during disaster rescues in unchartered, risky environments could be prevented by rapidly deploying sensor robots that use semi-autonomous technology to explore the regions of disasters, provide surveillance to inform first responders, and assist in the rescue of victims until human first responders can arrive. Current emergency response procedures are time-consuming, requiring first responders to don protective suits and hand place sensors to obtain air quality readings. Current disaster robots cannot be rapidly deployed and can be ineffective in navigating surface obstacles and climbing steep slopes to reach areas of interest. Instead, tensegrity sensor robots dropped from aerial vehicles, such as drones or helicopters, can land in dangerous, often difficult-to-reach areas and immediately transmit surveillance and environmental data. With this information, first responder teams can better understand the situational hazards and plan how best to ameliorate the emergency saving lives, while reducing costs and property damage. This proposed technology will also have broader impact in use for scientific and commercial monitoring and surveillance as well. This Small Business Innovation Research (SBIR) Phase II project will advance the development of tensegrity robots, their durability, and their propulsion, de-risking the technology for the commercial market. This work will focus on expanding the features and structures of two robotic platforms: (1) stationary robots that provide persistent monitoring in one location and (2) mobile robots that are capable of ground travel over rough terrain (rubble, rocks, slopes). Finite element analysis/computational fluid dynamics simulations will be used to reduce the robots' weight and improve impact-resilience and portability. Software improvements will focus on enhancing speed capabilities and energy efficiency for rough terrain locomotion. Control engineers will integrate robust Model Predictive Control to improve path planning and enhance the robots' locomotion in a wide range of topologies and environments. Improved software algorithms and user interfaces will provide first responders with summarized data analytics for real-time assessments in the field as well as deliver cloud-server support. Integrated playback functionality and data-driven learning will improve post-situation evaluations. With technologies that provide live 360-degree video feeds and greater incident intelligence, this project will improve rescue outcomes in future disaster recovery operations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Tagged as:
SBIR
Phase II
2019
NSF
SBIR Phase I: Shape-shifting robots for Disaster Rescue, Monitoring, and Education
Amount: $225,000 Topic: EW
The broader impact/ commercial potential of this project is to commercialize previous research in tensegrity robots for new markets in disaster rescue, surveillance, scientific monitoring, and STEM (Science, Technology, Engineering and Math) education. Future deaths by both victims and first responders in disaster rescue in unchartered risky environments could be prevented by utilizing semi-autonomous technology to explore the regions of disasters, provide surveillance to inform first responders, and assist in the rescue of victims until human first responders can arrive. Current autonomous vehicles can be ineffective in navigating surface obstacles and climbing steep slopes to reach areas of interest. Aerial operations may be limited to dropping supplies, which may not be beneficial if victims are immobile or unconscious. The goal is to drop the proposed shape-shifting robots from aerial vehicles, so that these mobile robots can reach previously difficult areas for effective emergency response. This proposed technology will have broader impact in use for scientific monitoring and surveillance as well. A secondary market will be for K-12 students, teachers, parents and roboticists with the potential to have large impact in STEM education. Robot kits will be developed for educational applications that will meet new Next Generation Science Standards. The Small Business Innovation Research (SBIR) Phase I project will focus on de-risking prior research in the development of spherical tensegrity structures as a robotic platform for the proposed target applications. To meet market needs, the specifications need to include impact testing from a drop from an aerial vehicle along with ground travel requirements of slope, rubble and speed. New hardware and software will be designed to meet these specifications. The following three control algorithms and actuation schemes will be developed and evaluated for target specifications and tested in simulation and in hardware for locomotion (1) Multi-cable rolling motion on inclined surfaces, (2) Dynamic rolling using Model Predictive Control (MPC), and (3) Deep reinforcement learning. For applications where the terrain has been mapped, a (4) Generative path-planning algorithm will be developed. (5) Control mechanisms for the internal sphere of the robot will be developed so that the tensegrity robot will be able to manipulate and orient a payload of sensing equipment (e.g., camera, ultrasound, infrared, laser, spectrometer) while traveling on rough terrain. (6) Associated sensor validation, fusion and estimation techniques will be developed to meet the specifications. The results will be a proof-of-concept prototype that meets the target specifications.
Tagged as:
SBIR
Phase I
2018
NSF